Disintegration+and+Eysenck+Personality+Dimensions.rrstudio-user

Fri Jan 25 17:12:47 2019

# Install and load metaforinstall.packages("metafor")

## Installing package into '/home/rstudio-user/R/x86_64-pc-linux-gnu-library/3.5'## (as 'lib' is unspecified)library(metafor)

## Loading required package: Matrix

## Loading 'metafor' package (version 2.0-0). For an overview## and introduction to the package please type: help(metafor).# Data import via rio : https://cran.r-project.org/web/packages/rio/README.htmlinstall.packages("rio")

## Installing package into '/home/rstudio-user/R/x86_64-pc-linux-gnu-library/3.5'## (as 'lib' is unspecified)library("rio")

dat.analysis <- import("datAnalysis.csv")head(dat.analysis)

## V1 id.article id.study id.sample id.subsample year country.study## 1 1 101 1011 10111 101111 2013 Continental Europe## 2 2 101 1011 10111 101111 2013 Continental Europe## 3 3 101 1011 10111 101111 2013 Continental Europe## 4 4 102 1021 10211 102111 1988 Asia## 5 5 102 1021 10211 102111 1988 Asia## 6 6 102 1021 10211 102111 1988 Asia## language n.schizo male.percent1 age.mean1 age.min age.max n.control## 1 Non-English 60 68.33 40.865 23 55 35## 2 Non-English 60 68.33 40.865 23 55 35## 3 Non-English 60 68.33 40.865 23 55 35## 4 Non-English 78 100.00 33.000 NA NA 544## 5 Non-English 78 100.00 33.000 NA NA 544## 6 Non-English 78 100.00 33.000 NA NA 544## male.percent2 age.mean2 age.min2 age.max2 age.mean.all2## 1 57.14 37.829 25 55 39.746## 2 57.14 37.829 25 55 39.746## 3 57.14 37.829 25 55 39.746## 4 100.00 NA NA NA 33.000## 5 100.00 NA NA NA 33.000## 6 100.00 NA NA NA 33.000## sample.clinical sample.student## 1 3 - comparison of clinical and nonclinical 2 - nonstudent## 2 3 - comparison of clinical and nonclinical 2 - nonstudent## 3 3 - comparison of clinical and nonclinical 2 - nonstudent## 4 3 - comparison of clinical and nonclinical 2 - nonstudent

1

## 5 3 - comparison of clinical and nonclinical 2 - nonstudent## 6 3 - comparison of clinical and nonclinical 2 - nonstudent## longitudinal schizo.type schizo.measure posneg## 1 2 - transversal 4 - schizophrenia 2 - rating by expert 3-nonclassified## 2 2 - transversal 4 - schizophrenia 2 - rating by expert 3-nonclassified## 3 2 - transversal 4 - schizophrenia 2 - rating by expert 3-nonclassified## 4 2 - transversal 4 - schizophrenia 2 - rating by expert 3-nonclassified## 5 2 - transversal 4 - schizophrenia 2 - rating by expert 3-nonclassified## 6 2 - transversal 4 - schizophrenia 2 - rating by expert 3-nonclassified## schizoscore.type persmodel trait## 1 <NA> 1 - Eysenck 1 - Neuroticism## 2 <NA> 1 - Eysenck 2 - Extraversion## 3 <NA> 1 - Eysenck 3 - Psychoticism## 4 <NA> 1 - Eysenck 1 - Neuroticism## 5 <NA> 1 - Eysenck 2 - Extraversion## 6 <NA> 1 - Eysenck 3 - Psychoticism## schizo.core schizo.neurot score.type es.measure r## 1 1 - core schizotypy content 1 - schizo 1 - Summative 2 - Cohen's d NA## 2 1 - core schizotypy content 1 - schizo 1 - Summative 2 - Cohen's d NA## 3 1 - core schizotypy content 1 - schizo 1 - Summative 2 - Cohen's d NA## 4 1 - core schizotypy content 1 - schizo 1 - Summative 2 - Cohen's d NA## 5 1 - core schizotypy content 1 - schizo 1 - Summative 2 - Cohen's d NA## 6 1 - core schizotypy content 1 - schizo 1 - Summative 2 - Cohen's d NA## m.schizo sd.schizo m.control sd.control study es weight## 1 8.80 4.70 7.40 5.00 NA 0.1389846 95.07351## 2 10.80 4.60 13.70 4.00 NA -0.3036019 91.41020## 3 7.00 3.10 3.00 1.30 NA 0.5972383 75.37945## 4 13.09 4.13 8.51 4.20 NA 0.3402849 584.77503## 5 8.69 3.10 10.34 3.32 NA -0.1636775 614.55509## 6 6.31 3.64 3.25 2.81 NA 0.3272768 587.80382## sample.size se var ci.lo ci.hi fishers.z## 1 95 0.10255816 0.010518177 -0.0610443 0.32828094 0.1398900## 2 95 0.10459301 0.010939698 -0.4765268 -0.10806034 -0.3134825## 3 95 0.11517906 0.013266216 0.4326044 0.72332798 0.6888431## 4 622 0.04135286 0.001710059 0.2667528 0.40987817 0.3544147## 5 622 0.04033849 0.001627193 -0.2394825 -0.08588897 -0.1651631## 6 622 0.04124619 0.001701248 0.2532985 0.39744958 0.3397754## ci.lo.z ci.hi.z measure## 1 -0.06112029 0.34090033 r## 2 -0.51848100 -0.10848392 r## 3 0.46309628 0.91458990 r## 4 0.27336453 0.43546478 r## 5 -0.24422507 -0.08610111 r## 6 0.25893431 0.42061639 r# Overall mean correlation and predicted values: Fit a random effects modelres.re <- rma(es, var, data=dat.analysis)res.re

#### Random-Effects Model (k = 350; tau^2 estimator: REML)#### tau^2 (estimated amount of total heterogeneity): 0.0566 (SE = 0.0048)## tau (square root of estimated tau^2 value): 0.2380## I^2 (total heterogeneity / total variability): 95.69%

2

## H^2 (total variability / sampling variability): 23.20#### Test for Heterogeneity:## Q(df = 349) = 9676.7480, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb ci.ub## 0.1458 0.0135 10.8334 <.0001 0.1194 0.1722 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1predict(res.re)

## pred se ci.lb ci.ub cr.lb cr.ub## 0.1458 0.0135 0.1194 0.1722 -0.3214 0.6130# Display forest plotforest(res.re)

RE Model

−1.5 −1 −0.5 0 0.5 1 1.5

Observed Outcome

Study 350Study 349Study 348Study 347Study 346Study 345Study 344Study 343Study 342Study 341Study 340Study 339Study 338Study 337Study 336Study 335Study 334Study 333Study 332Study 331Study 330Study 329Study 328Study 327Study 326Study 325Study 324Study 323Study 322Study 321Study 320Study 319Study 318Study 317Study 316Study 315Study 314Study 313Study 312Study 311Study 310Study 309Study 308Study 307Study 306Study 305Study 304Study 303Study 302Study 301Study 300Study 299Study 298Study 297Study 296Study 295Study 294Study 293Study 292Study 291Study 290Study 289Study 288Study 287Study 286Study 285Study 284Study 283Study 282Study 281Study 280Study 279Study 278Study 277Study 276Study 275Study 274Study 273Study 272Study 271Study 270Study 269Study 268Study 267Study 266Study 265Study 264Study 263Study 262Study 261Study 260Study 259Study 258Study 257Study 256Study 255Study 254Study 253Study 252Study 251Study 250Study 249Study 248Study 247Study 246Study 245Study 244Study 243Study 242Study 241Study 240Study 239Study 238Study 237Study 236Study 235Study 234Study 233Study 232Study 231Study 230Study 229Study 228Study 227Study 226Study 225Study 224Study 223Study 222Study 221Study 220Study 219Study 218Study 217Study 216Study 215Study 214Study 213Study 212Study 211Study 210Study 209Study 208Study 207Study 206Study 205Study 204Study 203Study 202Study 201Study 200Study 199Study 198Study 197Study 196Study 195Study 194Study 193Study 192Study 191Study 190Study 189Study 188Study 187Study 186Study 185Study 184Study 183Study 182Study 181Study 180Study 179Study 178Study 177Study 176Study 175Study 174Study 173Study 172Study 171Study 170Study 169Study 168Study 167Study 166Study 165Study 164Study 163Study 162Study 161Study 160Study 159Study 158Study 157Study 156Study 155Study 154Study 153Study 152Study 151Study 150Study 149Study 148Study 147Study 146Study 145Study 144Study 143Study 142Study 141Study 140Study 139Study 138Study 137Study 136Study 135Study 134Study 133Study 132Study 131Study 130Study 129Study 128Study 127Study 126Study 125Study 124Study 123Study 122Study 121Study 120Study 119Study 118Study 117Study 116Study 115Study 114Study 113Study 112Study 111Study 110Study 109Study 108Study 107Study 106Study 105Study 104Study 103Study 102Study 101Study 100Study 99Study 98Study 97Study 96Study 95Study 94Study 93Study 92Study 91Study 90Study 89Study 88Study 87Study 86Study 85Study 84Study 83Study 82Study 81Study 80Study 79Study 78Study 77Study 76Study 75Study 74Study 73Study 72Study 71Study 70Study 69Study 68Study 67Study 66Study 65Study 64Study 63Study 62Study 61Study 60Study 59Study 58Study 57Study 56Study 55Study 54Study 53Study 52Study 51Study 50Study 49Study 48Study 47Study 46Study 45Study 44Study 43Study 42Study 41Study 40Study 39Study 38Study 37Study 36Study 35Study 34Study 33Study 32Study 31Study 30Study 29Study 28Study 27Study 26Study 25Study 24Study 23Study 22Study 21Study 20Study 19Study 18Study 17Study 16Study 15Study 14Study 13Study 12Study 11Study 10Study 9Study 8Study 7Study 6Study 5Study 4Study 3Study 2Study 1

0.35 [ 0.17, 0.53]−0.25 [−0.42, −0.07] 0.23 [ 0.06, 0.41] 0.30 [ 0.12, 0.48]−0.27 [−0.45, −0.09] 0.29 [ 0.11, 0.47] 0.06 [−0.08, 0.20]−0.22 [−0.36, −0.07] 0.30 [ 0.16, 0.45]−0.14 [−0.24, −0.05] 0.15 [ 0.05, 0.25]−0.08 [−0.17, 0.02]−0.15 [−0.27, −0.04] 0.03 [−0.07, 0.12] 0.28 [ 0.16, 0.40] 0.11 [ 0.01, 0.21] 0.08 [−0.02, 0.18] 0.02 [−0.08, 0.12]−0.11 [−0.21, −0.01] 0.47 [ 0.39, 0.55] 0.00 [−0.10, 0.10] 0.01 [−0.13, 0.15] 0.00 [−0.14, 0.14] 0.37 [ 0.25, 0.49] 0.13 [−0.07, 0.33] 0.07 [−0.13, 0.27]−0.08 [−0.28, 0.12]−0.28 [−0.47, −0.09] 0.43 [ 0.27, 0.59] 0.22 [ 0.03, 0.41] 0.53 [ 0.44, 0.62] 0.03 [−0.10, 0.16] 0.26 [ 0.14, 0.38] 0.07 [−0.13, 0.27]−0.41 [−0.57, −0.25] 0.80 [ 0.73, 0.87] 0.55 [ 0.41, 0.69] 0.25 [ 0.07, 0.43] 0.21 [ 0.02, 0.40] 0.26 [ 0.08, 0.44] 0.36 [ 0.19, 0.53]−0.59 [−0.72, −0.46] 0.14 [−0.05, 0.33]−0.28 [−0.46, −0.10] 0.56 [ 0.42, 0.70] 0.23 [ 0.04, 0.42]−0.13 [−0.32, 0.06] 0.37 [ 0.20, 0.54] 0.31 [ 0.11, 0.50]−0.24 [−0.44, −0.05] 0.43 [ 0.23, 0.63]−0.01 [−0.06, 0.04]−0.19 [−0.24, −0.14] 0.05 [−0.00, 0.10] 0.27 [ 0.22, 0.32] 0.35 [ 0.30, 0.40] 0.07 [ 0.02, 0.12] 0.12 [ 0.07, 0.17]−0.32 [−0.37, −0.27] 0.11 [ 0.06, 0.16] 0.08 [ 0.03, 0.13] 0.06 [ 0.01, 0.11] 0.38 [ 0.33, 0.43]−0.01 [−0.05, 0.03]−0.17 [−0.21, −0.13] 0.07 [ 0.03, 0.11] 0.30 [ 0.26, 0.34] 0.36 [ 0.32, 0.40] 0.05 [ 0.01, 0.09] 0.07 [ 0.03, 0.11]−0.31 [−0.35, −0.27] 0.16 [ 0.12, 0.20] 0.15 [ 0.11, 0.19]−0.01 [−0.05, 0.03] 0.32 [ 0.28, 0.36] 0.28 [ 0.14, 0.42]−0.07 [−0.22, 0.08] 0.58 [ 0.48, 0.68] 0.43 [ 0.11, 0.75] 0.08 [−0.31, 0.47] 0.47 [ 0.17, 0.78] 0.14 [−0.11, 0.39]−0.28 [−0.54, −0.03] 0.45 [ 0.18, 0.71] 0.14 [−0.14, 0.42] 0.15 [−0.13, 0.43] 0.13 [−0.01, 0.27] 0.37 [ 0.25, 0.49] 0.23 [ 0.10, 0.36] 0.13 [−0.01, 0.27] 0.28 [ 0.14, 0.43] 0.17 [ 0.01, 0.32]−0.16 [−0.32, −0.00] 0.15 [ 0.05, 0.25]−0.23 [−0.33, −0.13] 0.08 [−0.02, 0.19] 0.21 [ 0.11, 0.31]−0.50 [−0.58, −0.42] 0.21 [ 0.11, 0.31] 0.20 [ 0.10, 0.30] 0.02 [−0.09, 0.12] 0.37 [ 0.28, 0.46] 0.23 [ 0.13, 0.33]−0.14 [−0.24, −0.03] 0.67 [ 0.61, 0.73] 0.22 [ 0.13, 0.32]−0.08 [−0.18, 0.03] 0.34 [ 0.25, 0.43] 0.11 [ 0.01, 0.21]−0.25 [−0.35, −0.16] 0.01 [−0.09, 0.11] 0.31 [ 0.22, 0.40]−0.40 [−0.48, −0.31] 0.17 [ 0.07, 0.27] 0.23 [ 0.14, 0.33] 0.12 [ 0.02, 0.22] 0.34 [ 0.25, 0.43] 0.25 [ 0.16, 0.35] 0.01 [−0.10, 0.11] 0.58 [ 0.52, 0.65] 0.35 [ 0.26, 0.44]−0.04 [−0.14, 0.06] 0.34 [ 0.25, 0.43] 0.41 [ 0.04, 0.78] 0.31 [ 0.05, 0.57] 0.38 [ 0.21, 0.55] 0.33 [ 0.15, 0.51] 0.38 [ 0.21, 0.55]−0.13 [−0.33, 0.07] 0.45 [ 0.29, 0.61] 0.03 [−0.17, 0.23]−0.10 [−0.29, 0.09]−0.20 [−0.31, −0.09]−0.05 [−0.17, 0.07]−0.08 [−0.27, 0.11] 0.13 [−0.06, 0.32] 0.03 [−0.09, 0.15]−0.09 [−0.21, 0.03]−0.14 [−0.33, 0.05] 0.21 [−0.06, 0.48] 0.20 [−0.07, 0.48] 0.34 [ 0.09, 0.60] 0.19 [ 0.08, 0.29] 0.26 [ 0.15, 0.36] 0.20 [ 0.10, 0.31] 0.28 [ 0.11, 0.45] 0.44 [ 0.29, 0.59] 0.13 [−0.05, 0.31] 0.46 [ 0.32, 0.60] 0.32 [ 0.16, 0.48] 0.39 [ 0.23, 0.55] 0.26 [ 0.09, 0.43] 0.48 [ 0.34, 0.62] 0.12 [−0.10, 0.34] 0.27 [ 0.05, 0.49] 0.10 [−0.07, 0.27] 0.12 [−0.04, 0.29] 0.57 [ 0.46, 0.68] 0.13 [−0.00, 0.26] 0.03 [−0.11, 0.17] 0.71 [ 0.64, 0.78] 0.29 [ 0.17, 0.41] 0.02 [−0.12, 0.16] 0.69 [ 0.62, 0.76] 0.25 [ 0.12, 0.38] 0.04 [−0.10, 0.18] 0.24 [ 0.11, 0.37] 0.23 [ 0.10, 0.36] 0.16 [ 0.03, 0.29] 0.57 [ 0.48, 0.66] 0.05 [−0.02, 0.12] 0.67 [ 0.63, 0.71] 0.32 [ 0.26, 0.38] 0.34 [ 0.28, 0.40] 0.01 [−0.07, 0.09] 0.68 [ 0.64, 0.72] 0.32 [ 0.25, 0.39] 0.33 [ 0.26, 0.40] 0.23 [ 0.12, 0.34]−0.01 [−0.12, 0.10] 0.28 [ 0.17, 0.39]−0.02 [−0.17, 0.13]−0.36 [−0.49, −0.23] 0.00 [−0.15, 0.15] 0.15 [ 0.01, 0.29]−0.40 [−0.52, −0.28] 0.14 [−0.00, 0.28] 0.34 [ 0.21, 0.47] 0.03 [−0.12, 0.18] 0.33 [ 0.20, 0.46] 0.25 [ 0.11, 0.39]−0.07 [−0.22, 0.08] 0.64 [ 0.55, 0.73] 0.17 [ 0.03, 0.31] 0.12 [−0.02, 0.26]−0.12 [−0.26, 0.02] 0.31 [ 0.18, 0.44] 0.19 [ 0.05, 0.33] 0.06 [−0.09, 0.21] 0.34 [ 0.21, 0.47] 0.04 [−0.11, 0.19] 0.13 [−0.01, 0.27] 0.30 [ 0.17, 0.43]−0.05 [−0.20, 0.10] 0.35 [ 0.22, 0.48] 0.01 [−0.14, 0.16]−0.32 [−0.45, −0.19] 0.45 [ 0.33, 0.57] 0.06 [−0.09, 0.21]−0.39 [−0.51, −0.27] 0.70 [ 0.63, 0.77] 0.28 [ 0.14, 0.42] 0.02 [−0.13, 0.17] 0.31 [ 0.18, 0.44] 0.49 [ 0.38, 0.60] 0.30 [ 0.17, 0.43] 0.27 [ 0.13, 0.41] 0.25 [ 0.11, 0.39]−0.04 [−0.19, 0.11] 0.32 [ 0.19, 0.45] 0.22 [−0.04, 0.48] 0.11 [−0.16, 0.38] 0.18 [−0.13, 0.49]−0.36 [−0.68, −0.04] 0.74 [ 0.36, 1.13]−0.19 [−0.50, 0.11]−0.72 [−1.10, −0.34] 0.88 [ 0.39, 1.36]−0.13 [−0.32, 0.06] 0.02 [−0.17, 0.21] 0.28 [ 0.10, 0.46]−0.40 [−0.64, −0.16]−0.24 [−0.51, 0.03] 0.24 [−0.03, 0.51]−0.19 [−0.46, 0.09]−0.24 [−0.51, 0.03] 0.24 [−0.03, 0.51]−0.29 [−0.56, −0.03]−0.24 [−0.51, 0.03] 0.24 [−0.03, 0.51]−0.19 [−0.49, 0.11]−0.26 [−0.56, 0.03] 0.26 [−0.03, 0.56]−0.00 [−0.32, 0.31]−0.26 [−0.56, 0.03] 0.26 [−0.03, 0.56]−0.11 [−0.42, 0.20]−0.26 [−0.56, 0.03] 0.26 [−0.03, 0.56] 0.22 [−0.04, 0.48] 0.26 [ 0.16, 0.36] 0.59 [ 0.52, 0.66] 0.43 [ 0.31, 0.55] 0.05 [−0.09, 0.19] 0.44 [ 0.32, 0.56]−0.49 [−0.75, −0.23] 0.38 [ 0.09, 0.67]−0.14 [−0.30, 0.02] 0.23 [ 0.07, 0.39] 0.12 [−0.10, 0.34] 0.09 [−0.14, 0.32] 0.00 [−0.29, 0.29]−0.04 [−0.33, 0.25] 0.26 [ 0.03, 0.50]−0.31 [−0.55, −0.07] 0.36 [ 0.12, 0.60] 0.31 [ 0.13, 0.49] 0.20 [ 0.00, 0.40] 0.58 [ 0.44, 0.72] 0.35 [ 0.17, 0.53] 0.20 [ 0.00, 0.40] 0.29 [ 0.10, 0.48] 0.16 [ 0.03, 0.29]−0.01 [−0.14, 0.13] 0.17 [ 0.04, 0.30] 0.20 [ 0.07, 0.33]−0.14 [−0.27, −0.01] 0.12 [−0.01, 0.25] 0.13 [ 0.00, 0.27] 0.03 [−0.11, 0.16] 0.01 [−0.13, 0.14] 0.06 [−0.08, 0.19] 0.03 [−0.10, 0.17] 0.10 [−0.04, 0.23]−0.06 [−0.16, 0.05] 0.43 [ 0.35, 0.52] 0.00 [−0.10, 0.10] 0.16 [ 0.05, 0.26] 0.24 [ 0.14, 0.33] 0.20 [ 0.10, 0.30] 0.06 [−0.04, 0.16] 0.21 [ 0.11, 0.31] 0.06 [−0.01, 0.13]−0.23 [−0.30, −0.17] 0.56 [ 0.51, 0.61] 0.31 [ 0.24, 0.37] 0.10 [ 0.03, 0.17] 0.36 [ 0.30, 0.42] 0.06 [−0.01, 0.13]−0.39 [−0.45, −0.33] 0.25 [ 0.18, 0.32] 0.16 [ 0.09, 0.23] 0.06 [−0.02, 0.13] 0.33 [ 0.26, 0.39] 0.40 [ 0.02, 0.78]−0.27 [−0.69, 0.15] 0.32 [−0.08, 0.72] 0.26 [ 0.15, 0.37]−0.16 [−0.28, −0.04] 0.08 [−0.04, 0.20] 0.52 [ 0.43, 0.61] 0.10 [−0.02, 0.22] 0.34 [ 0.23, 0.45] 0.17 [ 0.06, 0.28]−0.26 [−0.36, −0.16] 0.43 [ 0.34, 0.52] 0.25 [ 0.14, 0.36] 0.04 [−0.08, 0.16] 0.32 [ 0.21, 0.43] 0.30 [ 0.20, 0.40] 0.48 [ 0.40, 0.56] 0.15 [ 0.04, 0.26]−0.23 [−0.48, 0.02]−0.51 [−0.70, −0.32] 0.11 [−0.15, 0.37] 0.12 [ 0.04, 0.20]−0.04 [−0.12, 0.04] 0.38 [ 0.31, 0.45] 0.32 [ 0.03, 0.61] 0.29 [ 0.08, 0.50] 0.36 [ 0.16, 0.56] 0.15 [−0.16, 0.46] 0.18 [−0.04, 0.40]−0.09 [−0.41, 0.23] 0.33 [ 0.13, 0.53]−0.05 [−0.37, 0.27] 0.32 [ 0.12, 0.52] 0.14 [−0.18, 0.46] 0.27 [ 0.12, 0.42] 0.37 [ 0.23, 0.51] 0.22 [−0.10, 0.54] 0.39 [ 0.30, 0.47]−0.23 [−0.32, −0.15] 0.30 [ 0.21, 0.38] 0.33 [ 0.25, 0.41]−0.16 [−0.24, −0.08] 0.34 [ 0.26, 0.42] 0.60 [ 0.37, 0.82]−0.30 [−0.51, −0.10] 0.14 [−0.06, 0.34]

0.15 [ 0.12, 0.17]

# Display funnel plotfunnel(res.re)

3

Observed Outcome

Sta

ndar

d E

rror

0.24

90.

187

0.12

40.

062

0

−0.5 0 0.5 1

# Publication bias assessment: Regression test for funnel plot asymmetryregtest(res.re, model="lm")

#### Regression Test for Funnel Plot Asymmetry#### model: weighted regression with multiplicative dispersion## predictor: standard error#### test for funnel plot asymmetry: t = -1.8223, df = 348, p = 0.0693# Mean corr: PP <> Neuroticism ####res.re.n <- rma(es, var, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n

#### Random-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of total heterogeneity): 0.0369 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1920## I^2 (total heterogeneity / total variability): 93.98%## H^2 (total variability / sampling variability): 16.60#### Test for Heterogeneity:## Q(df = 110) = 2180.5092, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb ci.ub## 0.2951 0.0196 15.0693 <.0001 0.2567 0.3334 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

4

predict(res.re.n)

## pred se ci.lb ci.ub cr.lb cr.ub## 0.2951 0.0196 0.2567 0.3334 -0.0831 0.6733# display forest plotforest(res.re.n)

RE Model

−0.5 0 0.5 1 1.5

Observed Outcome

Study 348Study 345Study 342Study 340Study 337Study 336Study 331Study 330Study 327Study 322Study 321Study 318Study 315Study 312Study 310Study 306Study 303Study 300Study 297Study 294Study 291Study 288Study 285Study 282Study 279Study 276Study 273Study 270Study 267Study 258Study 255Study 252Study 249Study 246Study 243Study 240Study 237Study 234Study 231Study 228Study 221Study 220Study 217Study 216Study 213Study 212Study 209Study 207Study 204Study 202Study 200Study 198Study 196Study 193Study 190Study 187Study 185Study 183Study 181Study 167Study 164Study 161Study 158Study 156Study 153Study 149Study 146Study 143Study 140Study 137Study 134Study 131Study 126Study 123Study 120Study 117Study 114Study 111Study 108Study 105Study 102Study 99Study 96Study 94Study 92Study 85Study 82Study 79Study 76Study 73Study 70Study 67Study 65Study 63Study 61Study 59Study 56Study 53Study 50Study 47Study 44Study 41Study 38Study 35Study 32Study 29Study 26Study 23Study 7Study 4Study 1

0.23 [ 0.06, 0.41] 0.29 [ 0.11, 0.47] 0.30 [ 0.16, 0.45] 0.15 [ 0.05, 0.25]

0.03 [−0.07, 0.12] 0.28 [ 0.16, 0.40] 0.47 [ 0.39, 0.55]

0.00 [−0.10, 0.10] 0.37 [ 0.25, 0.49] 0.43 [ 0.27, 0.59] 0.22 [ 0.03, 0.41] 0.26 [ 0.14, 0.38] 0.80 [ 0.73, 0.87] 0.21 [ 0.02, 0.40] 0.36 [ 0.19, 0.53] 0.56 [ 0.42, 0.70] 0.37 [ 0.20, 0.54] 0.43 [ 0.23, 0.63]

0.05 [−0.00, 0.10] 0.07 [ 0.02, 0.12] 0.11 [ 0.06, 0.16] 0.38 [ 0.33, 0.43] 0.07 [ 0.03, 0.11] 0.05 [ 0.01, 0.09] 0.16 [ 0.12, 0.20] 0.32 [ 0.28, 0.36] 0.58 [ 0.48, 0.68] 0.47 [ 0.17, 0.78] 0.45 [ 0.18, 0.71]

−0.16 [−0.32, −0.00] 0.08 [−0.02, 0.19] 0.21 [ 0.11, 0.31] 0.37 [ 0.28, 0.46] 0.67 [ 0.61, 0.73] 0.34 [ 0.25, 0.43]

0.01 [−0.09, 0.11] 0.17 [ 0.07, 0.27] 0.34 [ 0.25, 0.43] 0.58 [ 0.52, 0.65] 0.34 [ 0.25, 0.43] 0.45 [ 0.29, 0.61]

0.03 [−0.17, 0.23]−0.05 [−0.17, 0.07]−0.08 [−0.27, 0.11]−0.09 [−0.21, 0.03]−0.14 [−0.33, 0.05]

0.34 [ 0.09, 0.60] 0.26 [ 0.15, 0.36] 0.44 [ 0.29, 0.59] 0.46 [ 0.32, 0.60] 0.39 [ 0.23, 0.55] 0.48 [ 0.34, 0.62] 0.27 [ 0.05, 0.49] 0.57 [ 0.46, 0.68] 0.71 [ 0.64, 0.78] 0.69 [ 0.62, 0.76]

0.04 [−0.10, 0.18] 0.23 [ 0.10, 0.36] 0.57 [ 0.48, 0.66]

0.00 [−0.15, 0.15] 0.14 [−0.00, 0.28] 0.33 [ 0.20, 0.46] 0.64 [ 0.55, 0.73]

0.12 [−0.02, 0.26] 0.19 [ 0.05, 0.33]

0.13 [−0.01, 0.27] 0.35 [ 0.22, 0.48] 0.45 [ 0.33, 0.57] 0.70 [ 0.63, 0.77] 0.31 [ 0.18, 0.44] 0.27 [ 0.13, 0.41] 0.32 [ 0.19, 0.45] 0.74 [ 0.36, 1.13] 0.88 [ 0.39, 1.36] 0.28 [ 0.10, 0.46]

0.24 [−0.03, 0.51] 0.24 [−0.03, 0.51] 0.24 [−0.03, 0.51] 0.26 [−0.03, 0.56] 0.26 [−0.03, 0.56] 0.26 [−0.03, 0.56] 0.59 [ 0.52, 0.66] 0.44 [ 0.32, 0.56] 0.38 [ 0.09, 0.67] 0.23 [ 0.07, 0.39] 0.36 [ 0.12, 0.60] 0.58 [ 0.44, 0.72] 0.29 [ 0.10, 0.48] 0.17 [ 0.04, 0.30]

0.12 [−0.01, 0.25] 0.01 [−0.13, 0.14] 0.10 [−0.04, 0.23] 0.43 [ 0.35, 0.52] 0.16 [ 0.05, 0.26] 0.20 [ 0.10, 0.30] 0.21 [ 0.11, 0.31] 0.56 [ 0.51, 0.61] 0.36 [ 0.30, 0.42] 0.25 [ 0.18, 0.32] 0.33 [ 0.26, 0.39]

0.32 [−0.08, 0.72] 0.08 [−0.04, 0.20] 0.34 [ 0.23, 0.45] 0.43 [ 0.34, 0.52] 0.32 [ 0.21, 0.43] 0.15 [ 0.04, 0.26]

0.11 [−0.15, 0.37] 0.38 [ 0.31, 0.45] 0.30 [ 0.21, 0.38] 0.34 [ 0.26, 0.42]

0.14 [−0.06, 0.34]

0.30 [ 0.26, 0.33]

# display funnel plotfunnel(res.re.n)

Observed Outcome

Sta

ndar

d E

rror

0.24

90.

187

0.12

40.

062

0

−0.2 −0 0.2 0.4 0.6 0.8 1

5

# Publication bias assessment: Regression test for funnel plot asymmetryregtest(res.re.n, model="lm")

#### Regression Test for Funnel Plot Asymmetry#### model: weighted regression with multiplicative dispersion## predictor: standard error#### test for funnel plot asymmetry: t = -0.2300, df = 109, p = 0.8186# Moderators: PP <> Neuroticism ####

## All moderators included simultaneouslyres.re.n.metareg <- rma(es, var, mods = ~ factor(sample.clinical)

+ factor(sample.student)+ factor(schizo.measure)+ factor(posneg)+ factor(es.measure)+ factor(country.study)+ factor(language)+ factor (schizo.core)+ factor (schizo.neurot)+ year+ age.mean.all2, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))

## Warning in rma(es, var, mods = ~factor(sample.clinical) +## factor(sample.student) + : Studies with NAs omitted from model fitting.

## Warning in rma(es, var, mods = ~factor(sample.clinical) +## factor(sample.student) + : Redundant predictors dropped from the model.res.re.n.metareg

#### Mixed-Effects Model (k = 88; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0159 (SE = 0.0036)## tau (square root of estimated tau^2 value): 0.1260## I^2 (residual heterogeneity / unaccounted variability): 81.49%## H^2 (unaccounted variability / sampling variability): 5.40## R^2 (amount of heterogeneity accounted for): 44.58%#### Test for Residual Heterogeneity:## QE(df = 68) = 405.1855, p-val < .0001#### Test of Moderators (coefficient(s) 2:20):## QM(df = 19) = 70.0099, p-val < .0001#### Model Results:#### estimate## intrcpt -2.0790## factor(sample.clinical)2 - clinical -0.2299## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.4421## factor(sample.student)2 - nonstudent 0.0501

6

## factor(sample.student)3 - combined student and nonstudent -0.0228## factor(schizo.measure)2 - rating by expert -0.0545## factor(posneg)2-negative -0.1462## factor(posneg)3-nonclassified 0.3472## factor(country.study)Australia and NZ -0.0227## factor(country.study)Continental Europe -0.0087## factor(country.study)South America -0.1519## factor(country.study)UK -0.0536## factor(country.study)USA -0.0428## factor(language)Non-English -0.0186## factor(schizo.core)2 - strong correlate but not core (E-) -0.0112## factor(schizo.core)3 - weak correlate but not core (C-, A-) -0.4576## factor(schizo.core)4 - neither core nor correlate -0.1957## factor(schizo.neurot)2 - neurot 0.2226## year 0.0013## age.mean.all2 0.0002## se## intrcpt 4.0908## factor(sample.clinical)2 - clinical 0.1143## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.1616## factor(sample.student)2 - nonstudent 0.0787## factor(sample.student)3 - combined student and nonstudent 0.0583## factor(schizo.measure)2 - rating by expert 0.0909## factor(posneg)2-negative 0.0718## factor(posneg)3-nonclassified 0.1367## factor(country.study)Australia and NZ 0.1447## factor(country.study)Continental Europe 0.1013## factor(country.study)South America 0.1324## factor(country.study)UK 0.1327## factor(country.study)USA 0.1208## factor(language)Non-English 0.0869## factor(schizo.core)2 - strong correlate but not core (E-) 0.0920## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.1577## factor(schizo.core)4 - neither core nor correlate 0.0943## factor(schizo.neurot)2 - neurot 0.0877## year 0.0021## age.mean.all2 0.0053## zval## intrcpt -0.5082## factor(sample.clinical)2 - clinical -2.0111## factor(sample.clinical)3 - comparison of clinical and nonclinical -2.7364## factor(sample.student)2 - nonstudent 0.6364## factor(sample.student)3 - combined student and nonstudent -0.3918## factor(schizo.measure)2 - rating by expert -0.5994## factor(posneg)2-negative -2.0379## factor(posneg)3-nonclassified 2.5407## factor(country.study)Australia and NZ -0.1569## factor(country.study)Continental Europe -0.0856## factor(country.study)South America -1.1475## factor(country.study)UK -0.4042## factor(country.study)USA -0.3542## factor(language)Non-English -0.2146## factor(schizo.core)2 - strong correlate but not core (E-) -0.1221## factor(schizo.core)3 - weak correlate but not core (C-, A-) -2.9016

7

## factor(schizo.core)4 - neither core nor correlate -2.0743## factor(schizo.neurot)2 - neurot 2.5364## year 0.6071## age.mean.all2 0.0452## pval## intrcpt 0.6113## factor(sample.clinical)2 - clinical 0.0443## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0062## factor(sample.student)2 - nonstudent 0.5245## factor(sample.student)3 - combined student and nonstudent 0.6952## factor(schizo.measure)2 - rating by expert 0.5489## factor(posneg)2-negative 0.0416## factor(posneg)3-nonclassified 0.0111## factor(country.study)Australia and NZ 0.8753## factor(country.study)Continental Europe 0.9318## factor(country.study)South America 0.2512## factor(country.study)UK 0.6860## factor(country.study)USA 0.7232## factor(language)Non-English 0.8301## factor(schizo.core)2 - strong correlate but not core (E-) 0.9029## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0037## factor(schizo.core)4 - neither core nor correlate 0.0380## factor(schizo.neurot)2 - neurot 0.0112## year 0.5438## age.mean.all2 0.9639## ci.lb## intrcpt -10.0968## factor(sample.clinical)2 - clinical -0.4539## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.7587## factor(sample.student)2 - nonstudent -0.1042## factor(sample.student)3 - combined student and nonstudent -0.1370## factor(schizo.measure)2 - rating by expert -0.2327## factor(posneg)2-negative -0.2869## factor(posneg)3-nonclassified 0.0794## factor(country.study)Australia and NZ -0.3064## factor(country.study)Continental Europe -0.2072## factor(country.study)South America -0.4113## factor(country.study)UK -0.3137## factor(country.study)USA -0.2795## factor(language)Non-English -0.1890## factor(schizo.core)2 - strong correlate but not core (E-) -0.1915## factor(schizo.core)3 - weak correlate but not core (C-, A-) -0.7668## factor(schizo.core)4 - neither core nor correlate -0.3806## factor(schizo.neurot)2 - neurot 0.0506## year -0.0028## age.mean.all2 -0.0102## ci.ub## intrcpt 5.9388## factor(sample.clinical)2 - clinical -0.0058## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.1254## factor(sample.student)2 - nonstudent 0.2044## factor(sample.student)3 - combined student and nonstudent 0.0914## factor(schizo.measure)2 - rating by expert 0.1237## factor(posneg)2-negative -0.0056

8

## factor(posneg)3-nonclassified 0.6151## factor(country.study)Australia and NZ 0.2609## factor(country.study)Continental Europe 0.1899## factor(country.study)South America 0.1075## factor(country.study)UK 0.2065## factor(country.study)USA 0.1940## factor(language)Non-English 0.1517## factor(schizo.core)2 - strong correlate but not core (E-) 0.1691## factor(schizo.core)3 - weak correlate but not core (C-, A-) -0.1485## factor(schizo.core)4 - neither core nor correlate -0.0108## factor(schizo.neurot)2 - neurot 0.3945## year 0.0053## age.mean.all2 0.0107#### intrcpt## factor(sample.clinical)2 - clinical *## factor(sample.clinical)3 - comparison of clinical and nonclinical **## factor(sample.student)2 - nonstudent## factor(sample.student)3 - combined student and nonstudent## factor(schizo.measure)2 - rating by expert## factor(posneg)2-negative *## factor(posneg)3-nonclassified *## factor(country.study)Australia and NZ## factor(country.study)Continental Europe## factor(country.study)South America## factor(country.study)UK## factor(country.study)USA## factor(language)Non-English## factor(schizo.core)2 - strong correlate but not core (E-)## factor(schizo.core)3 - weak correlate but not core (C-, A-) **## factor(schizo.core)4 - neither core nor correlate *## factor(schizo.neurot)2 - neurot *## year## age.mean.all2#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.clinical <> Neuroticismres.re.n.sample.clinical <- rma(es, var, mods = ~ factor(sample.clinical)-1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.sample.clinical

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0323 (SE = 0.0051)## tau (square root of estimated tau^2 value): 0.1796## I^2 (residual heterogeneity / unaccounted variability): 93.21%## H^2 (unaccounted variability / sampling variability): 14.72#### Test for Residual Heterogeneity:## QE(df = 108) = 2048.1981, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 271.1948, p-val < .0001

9

#### Model Results:#### estimate## factor(sample.clinical)1 - nonclinical 0.3169## factor(sample.clinical)2 - clinical 0.0171## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.3012## se## factor(sample.clinical)1 - nonclinical 0.0207## factor(sample.clinical)2 - clinical 0.0722## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0499## zval## factor(sample.clinical)1 - nonclinical 15.3223## factor(sample.clinical)2 - clinical 0.2372## factor(sample.clinical)3 - comparison of clinical and nonclinical 6.0304## pval## factor(sample.clinical)1 - nonclinical <.0001## factor(sample.clinical)2 - clinical 0.8125## factor(sample.clinical)3 - comparison of clinical and nonclinical <.0001## ci.lb## factor(sample.clinical)1 - nonclinical 0.2764## factor(sample.clinical)2 - clinical -0.1244## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.2033## ci.ub## factor(sample.clinical)1 - nonclinical 0.3574## factor(sample.clinical)2 - clinical 0.1587## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.3990#### factor(sample.clinical)1 - nonclinical ***## factor(sample.clinical)2 - clinical## factor(sample.clinical)3 - comparison of clinical and nonclinical ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.clinical <> Neuroticism: Reference: nonclinical sampleres.re.n.sample.clinical.r <- rma(es, var, mods = ~ factor(sample.clinical), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.sample.clinical.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0323 (SE = 0.0051)## tau (square root of estimated tau^2 value): 0.1796## I^2 (residual heterogeneity / unaccounted variability): 93.21%## H^2 (unaccounted variability / sampling variability): 14.72## R^2 (amount of heterogeneity accounted for): 12.44%#### Test for Residual Heterogeneity:## QE(df = 108) = 2048.1981, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 15.9365, p-val = 0.0003#### Model Results:

10

#### estimate## intrcpt 0.3169## factor(sample.clinical)2 - clinical -0.2998## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.0157## se## intrcpt 0.0207## factor(sample.clinical)2 - clinical 0.0751## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0541## zval## intrcpt 15.3223## factor(sample.clinical)2 - clinical -3.9899## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.2909## pval## intrcpt <.0001## factor(sample.clinical)2 - clinical <.0001## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.7711## ci.lb## intrcpt 0.2764## factor(sample.clinical)2 - clinical -0.4470## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.1217## ci.ub## intrcpt 0.3574## factor(sample.clinical)2 - clinical -0.1525## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0902#### intrcpt ***## factor(sample.clinical)2 - clinical ***## factor(sample.clinical)3 - comparison of clinical and nonclinical#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.student <> Neuroticismres.re.n.sample.student <- rma(es, var, mods = ~ factor(sample.student) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.sample.student

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0361 (SE = 0.0056)## tau (square root of estimated tau^2 value): 0.1899## I^2 (residual heterogeneity / unaccounted variability): 93.78%## H^2 (unaccounted variability / sampling variability): 16.07#### Test for Residual Heterogeneity:## QE(df = 108) = 1945.3282, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 234.8673, p-val < .0001#### Model Results:#### estimate## factor(sample.student)1 - student 0.3351

11

## factor(sample.student)2 - nonstudent 0.2554## factor(sample.student)3 - combined student and nonstudent 0.2909## se zval## factor(sample.student)1 - student 0.0302 11.0976## factor(sample.student)2 - nonstudent 0.0308 8.2880## factor(sample.student)3 - combined student and nonstudent 0.0443 6.5589## pval ci.lb## factor(sample.student)1 - student <.0001 0.2759## factor(sample.student)2 - nonstudent <.0001 0.1950## factor(sample.student)3 - combined student and nonstudent <.0001 0.2039## ci.ub## factor(sample.student)1 - student 0.3942 ***## factor(sample.student)2 - nonstudent 0.3158 ***## factor(sample.student)3 - combined student and nonstudent 0.3778 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.student <> Neuroticism: Reference: student sampleres.re.n.sample.student.r <- rma(es, var, mods = ~ factor(sample.student), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.sample.student.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0361 (SE = 0.0056)## tau (square root of estimated tau^2 value): 0.1899## I^2 (residual heterogeneity / unaccounted variability): 93.78%## H^2 (unaccounted variability / sampling variability): 16.07## R^2 (amount of heterogeneity accounted for): 2.13%#### Test for Residual Heterogeneity:## QE(df = 108) = 1945.3282, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 3.4184, p-val = 0.1810#### Model Results:#### estimate## intrcpt 0.3351## factor(sample.student)2 - nonstudent -0.0796## factor(sample.student)3 - combined student and nonstudent -0.0442## se zval## intrcpt 0.0302 11.0976## factor(sample.student)2 - nonstudent 0.0431 -1.8459## factor(sample.student)3 - combined student and nonstudent 0.0536 -0.8240## pval ci.lb## intrcpt <.0001 0.2759## factor(sample.student)2 - nonstudent 0.0649 -0.1642## factor(sample.student)3 - combined student and nonstudent 0.4099 -0.1494## ci.ub## intrcpt 0.3942 ***## factor(sample.student)2 - nonstudent 0.0049 .## factor(sample.student)3 - combined student and nonstudent 0.0609

12

#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.measure <> Neuroticismres.re.n.schizo.measure <- rma(es, var, mods = ~ factor(schizo.measure) -1,data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.schizo.measure

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0370 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1924## I^2 (residual heterogeneity / unaccounted variability): 94.00%## H^2 (unaccounted variability / sampling variability): 16.67#### Test for Residual Heterogeneity:## QE(df = 109) = 2166.0280, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 226.3895, p-val < .0001#### Model Results:#### estimate se zval## factor(schizo.measure)1 - self-report 0.2977 0.0207 14.3639## factor(schizo.measure)2 - rating by expert 0.2722 0.0608 4.4798## pval ci.lb ci.ub## factor(schizo.measure)1 - self-report <.0001 0.2571 0.3384 ***## factor(schizo.measure)2 - rating by expert <.0001 0.1531 0.3912 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.measure <> Neuroticism: Reference: self-reportres.re.n.schizo.measure.r <- rma(es, var, mods = ~ factor(schizo.measure),data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.schizo.measure.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0370 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1924## I^2 (residual heterogeneity / unaccounted variability): 94.00%## H^2 (unaccounted variability / sampling variability): 16.67## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 109) = 2166.0280, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.1588, p-val = 0.6903#### Model Results:#### estimate se zval

13

## intrcpt 0.2977 0.0207 14.3639## factor(schizo.measure)2 - rating by expert -0.0256 0.0642 -0.3985## pval ci.lb ci.ub## intrcpt <.0001 0.2571 0.3384 ***## factor(schizo.measure)2 - rating by expert 0.6903 -0.1514 0.1002#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## posneg <> Neuroticismres.re.n.nosneg <- rma(es, var, mods = ~ factor(posneg) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.nosneg

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0260 (SE = 0.0042)## tau (square root of estimated tau^2 value): 0.1613## I^2 (residual heterogeneity / unaccounted variability): 91.46%## H^2 (unaccounted variability / sampling variability): 11.71#### Test for Residual Heterogeneity:## QE(df = 108) = 1268.6167, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 347.0922, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb## factor(posneg)1-positive 0.3807 0.0229 16.6076 <.0001 0.3358## factor(posneg)2-negative 0.1275 0.0334 3.8160 0.0001 0.0620## factor(posneg)3-nonclassified 0.2787 0.0370 7.5312 <.0001 0.2062## ci.ub## factor(posneg)1-positive 0.4256 ***## factor(posneg)2-negative 0.1930 ***## factor(posneg)3-nonclassified 0.3512 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## posneg <> Neuroticis: Reference: positiveres.re.n.nosneg.r <- rma(es, var, mods = ~ factor(posneg), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.nosneg.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0260 (SE = 0.0042)## tau (square root of estimated tau^2 value): 0.1613## I^2 (residual heterogeneity / unaccounted variability): 91.46%## H^2 (unaccounted variability / sampling variability): 11.71## R^2 (amount of heterogeneity accounted for): 29.43%#### Test for Residual Heterogeneity:## QE(df = 108) = 1268.6167, p-val < .0001

14

#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 39.2949, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb## intrcpt 0.3807 0.0229 16.6076 <.0001 0.3358## factor(posneg)2-negative -0.2532 0.0405 -6.2481 <.0001 -0.3326## factor(posneg)3-nonclassified -0.1020 0.0435 -2.3440 0.0191 -0.1873## ci.ub## intrcpt 0.4256 ***## factor(posneg)2-negative -0.1738 ***## factor(posneg)3-nonclassified -0.0167 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## es.measure <> Neuroticismres.re.n.es.measure <- rma(es, var, mods = ~ factor(es.measure) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.es.measure

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0372 (SE = 0.0058)## tau (square root of estimated tau^2 value): 0.1930## I^2 (residual heterogeneity / unaccounted variability): 94.03%## H^2 (unaccounted variability / sampling variability): 16.76#### Test for Residual Heterogeneity:## QE(df = 109) = 2169.9515, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 225.0346, p-val < .0001#### Model Results:#### estimate se zval pval## factor(es.measure)1 - correlation 0.2941 0.0211 13.9374 <.0001## factor(es.measure)2 - Cohen's d 0.3015 0.0543 5.5483 <.0001## ci.lb ci.ub## factor(es.measure)1 - correlation 0.2527 0.3355 ***## factor(es.measure)2 - Cohen's d 0.1950 0.4080 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## es.measure <> Neuroticism: Reference: correlationres.re.n.es.measure.r <- rma(es, var, mods = ~ factor(es.measure), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.es.measure.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0372 (SE = 0.0058)

15

## tau (square root of estimated tau^2 value): 0.1930## I^2 (residual heterogeneity / unaccounted variability): 94.03%## H^2 (unaccounted variability / sampling variability): 16.76## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 109) = 2169.9515, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.0161, p-val = 0.8991#### Model Results:#### estimate se zval pval## intrcpt 0.2941 0.0211 13.9374 <.0001## factor(es.measure)2 - Cohen's d 0.0074 0.0583 0.1268 0.8991## ci.lb ci.ub## intrcpt 0.2527 0.3355 ***## factor(es.measure)2 - Cohen's d -0.1069 0.1216#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## country.study <> Neuroticismres.re.n.country.study <- rma(es, var, mods = ~ factor(country.study) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.country.study

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0352 (SE = 0.0056)## tau (square root of estimated tau^2 value): 0.1875## I^2 (residual heterogeneity / unaccounted variability): 93.57%## H^2 (unaccounted variability / sampling variability): 15.56#### Test for Residual Heterogeneity:## QE(df = 104) = 1617.0765, p-val < .0001#### Test of Moderators (coefficient(s) 1:7):## QM(df = 7) = 246.1221, p-val < .0001#### Model Results:#### estimate se zval pval## factor(country.study)Asia 0.3329 0.1182 2.8173 0.0048## factor(country.study)Australia and NZ 0.1817 0.0558 3.2559 0.0011## factor(country.study)Continental Europe 0.2832 0.0384 7.3696 <.0001## factor(country.study)Israel 0.3440 0.2274 1.5128 0.1303## factor(country.study)South America 0.2010 0.0653 3.0764 0.0021## factor(country.study)UK 0.3470 0.0311 11.1552 <.0001## factor(country.study)USA 0.3208 0.0527 6.0894 <.0001## ci.lb ci.ub## factor(country.study)Asia 0.1013 0.5645 **## factor(country.study)Australia and NZ 0.0723 0.2910 **## factor(country.study)Continental Europe 0.2079 0.3585 ***

16

## factor(country.study)Israel -0.1017 0.7897## factor(country.study)South America 0.0729 0.3290 **## factor(country.study)UK 0.2860 0.4079 ***## factor(country.study)USA 0.2175 0.4240 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## country.study <> Neuroticism: Reference: Asiares.re.n.country.study.r <- rma(es, var, mods = ~ factor(country.study), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.country.study.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0352 (SE = 0.0056)## tau (square root of estimated tau^2 value): 0.1875## I^2 (residual heterogeneity / unaccounted variability): 93.57%## H^2 (unaccounted variability / sampling variability): 15.56## R^2 (amount of heterogeneity accounted for): 4.57%#### Test for Residual Heterogeneity:## QE(df = 104) = 1617.0765, p-val < .0001#### Test of Moderators (coefficient(s) 2:7):## QM(df = 6) = 9.4716, p-val = 0.1487#### Model Results:#### estimate se zval pval## intrcpt 0.3329 0.1182 2.8173 0.0048## factor(country.study)Australia and NZ -0.1512 0.1307 -1.1572 0.2472## factor(country.study)Continental Europe -0.0497 0.1242 -0.4000 0.6892## factor(country.study)Israel 0.0111 0.2563 0.0434 0.9654## factor(country.study)South America -0.1319 0.1350 -0.9771 0.3285## factor(country.study)UK 0.0141 0.1222 0.1153 0.9082## factor(country.study)USA -0.0121 0.1294 -0.0937 0.9253## ci.lb ci.ub## intrcpt 0.1013 0.5645 **## factor(country.study)Australia and NZ -0.4073 0.1049## factor(country.study)Continental Europe -0.2932 0.1938## factor(country.study)Israel -0.4911 0.5134## factor(country.study)South America -0.3965 0.1327## factor(country.study)UK -0.2254 0.2536## factor(country.study)USA -0.2657 0.2414#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## language <> Neuroticismres.re.n.language <- rma(es, var, mods = ~ factor(language) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.language

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)##

17

## tau^2 (estimated amount of residual heterogeneity): 0.0371 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1926## I^2 (residual heterogeneity / unaccounted variability): 93.96%## H^2 (unaccounted variability / sampling variability): 16.55#### Test for Residual Heterogeneity:## QE(df = 109) = 2149.0803, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 226.0327, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb## factor(language)English 0.3032 0.0257 11.8129 <.0001 0.2529## factor(language)Non-English 0.2836 0.0305 9.2998 <.0001 0.2238## ci.ub## factor(language)English 0.3535 ***## factor(language)Non-English 0.3434 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## language <> Neuroticism: Reference: Englishres.re.n.language.r <- rma(es, var, mods = ~ factor(language), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.language.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0371 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1926## I^2 (residual heterogeneity / unaccounted variability): 93.96%## H^2 (unaccounted variability / sampling variability): 16.55## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 109) = 2149.0803, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.2407, p-val = 0.6237#### Model Results:#### estimate se zval pval ci.lb## intrcpt 0.3032 0.0257 11.8129 <.0001 0.2529## factor(language)Non-English -0.0196 0.0399 -0.4907 0.6237 -0.0977## ci.ub## intrcpt 0.3535 ***## factor(language)Non-English 0.0586#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

18

## year <> Neuroticismres.re.n.year <- rma(es, var, mods = ~ year, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.year

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0372 (SE = 0.0058)## tau (square root of estimated tau^2 value): 0.1928## I^2 (residual heterogeneity / unaccounted variability): 94.00%## H^2 (unaccounted variability / sampling variability): 16.65## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 109) = 2165.0369, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.2365, p-val = 0.6268#### Model Results:#### estimate se zval pval ci.lb ci.ub## intrcpt 1.9400 3.3828 0.5735 0.5663 -4.6901 8.5701## year -0.0008 0.0017 -0.4863 0.6268 -0.0041 0.0025#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## age.mean.all2 <> Neuroticismres.re.n.age.mean.all2 <- rma(es, var, mods = ~ age.mean.all2, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))

## Warning in rma(es, var, mods = ~age.mean.all2, data = dat.analysis, subset## = (dat.analysis$trait == : Studies with NAs omitted from model fitting.res.re.n.age.mean.all2

#### Mixed-Effects Model (k = 88; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0290 (SE = 0.0053)## tau (square root of estimated tau^2 value): 0.1702## I^2 (residual heterogeneity / unaccounted variability): 90.10%## H^2 (unaccounted variability / sampling variability): 10.11## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 86) = 1024.6531, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.0267, p-val = 0.8701#### Model Results:#### estimate se zval pval ci.lb ci.ub## intrcpt 0.3420 0.0871 3.9283 <.0001 0.1714 0.5126 ***

19

## age.mean.all2 -0.0005 0.0032 -0.1635 0.8701 -0.0069 0.0058#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.core <> Neuroticismres.re.n.schizo.core <- rma(es, var, mods = ~ factor(schizo.core) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.schizo.core

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0297 (SE = 0.0048)## tau (square root of estimated tau^2 value): 0.1722## I^2 (residual heterogeneity / unaccounted variability): 92.21%## H^2 (unaccounted variability / sampling variability): 12.84#### Test for Residual Heterogeneity:## QE(df = 107) = 1313.3337, p-val < .0001#### Test of Moderators (coefficient(s) 1:4):## QM(df = 4) = 299.4509, p-val < .0001#### Model Results:#### estimate## factor(schizo.core)1 - core schizotypy content 0.3412## factor(schizo.core)2 - strong correlate but not core (E-) 0.1822## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.1855## factor(schizo.core)4 - neither core nor correlate 0.0480## se## factor(schizo.core)1 - core schizotypy content 0.0203## factor(schizo.core)2 - strong correlate but not core (E-) 0.0572## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0682## factor(schizo.core)4 - neither core nor correlate 0.0682## zval## factor(schizo.core)1 - core schizotypy content 16.7754## factor(schizo.core)2 - strong correlate but not core (E-) 3.1836## factor(schizo.core)3 - weak correlate but not core (C-, A-) 2.7216## factor(schizo.core)4 - neither core nor correlate 0.7043## pval## factor(schizo.core)1 - core schizotypy content <.0001## factor(schizo.core)2 - strong correlate but not core (E-) 0.0015## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0065## factor(schizo.core)4 - neither core nor correlate 0.4812## ci.lb## factor(schizo.core)1 - core schizotypy content 0.3014## factor(schizo.core)2 - strong correlate but not core (E-) 0.0700## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0519## factor(schizo.core)4 - neither core nor correlate -0.0856## ci.ub## factor(schizo.core)1 - core schizotypy content 0.3811 ***## factor(schizo.core)2 - strong correlate but not core (E-) 0.2943 **## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.3191 **## factor(schizo.core)4 - neither core nor correlate 0.1816

20

#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.core <> Neuroticism: Reference: core schizotypy contentres.re.n.schizo.core.r <- rma(es, var, mods = ~ factor(schizo.core), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.schizo.core.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0297 (SE = 0.0048)## tau (square root of estimated tau^2 value): 0.1722## I^2 (residual heterogeneity / unaccounted variability): 92.21%## H^2 (unaccounted variability / sampling variability): 12.84## R^2 (amount of heterogeneity accounted for): 19.50%#### Test for Residual Heterogeneity:## QE(df = 107) = 1313.3337, p-val < .0001#### Test of Moderators (coefficient(s) 2:4):## QM(df = 3) = 24.7604, p-val < .0001#### Model Results:#### estimate## intrcpt 0.3412## factor(schizo.core)2 - strong correlate but not core (E-) -0.1591## factor(schizo.core)3 - weak correlate but not core (C-, A-) -0.1557## factor(schizo.core)4 - neither core nor correlate -0.2932## se## intrcpt 0.0203## factor(schizo.core)2 - strong correlate but not core (E-) 0.0607## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0711## factor(schizo.core)4 - neither core nor correlate 0.0711## zval## intrcpt 16.7754## factor(schizo.core)2 - strong correlate but not core (E-) -2.6194## factor(schizo.core)3 - weak correlate but not core (C-, A-) -2.1890## factor(schizo.core)4 - neither core nor correlate -4.1216## pval## intrcpt <.0001## factor(schizo.core)2 - strong correlate but not core (E-) 0.0088## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0286## factor(schizo.core)4 - neither core nor correlate <.0001## ci.lb## intrcpt 0.3014## factor(schizo.core)2 - strong correlate but not core (E-) -0.2781## factor(schizo.core)3 - weak correlate but not core (C-, A-) -0.2952## factor(schizo.core)4 - neither core nor correlate -0.4327## ci.ub## intrcpt 0.3811 ***## factor(schizo.core)2 - strong correlate but not core (E-) -0.0400 **## factor(schizo.core)3 - weak correlate but not core (C-, A-) -0.0163 *## factor(schizo.core)4 - neither core nor correlate -0.1538 ***

21

#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.neurot <> Neuroticismres.re.n.schizo.neurot <- rma(es, var, mods = ~ factor(schizo.neurot) -1, data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.schizo.neurot

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0354 (SE = 0.0055)## tau (square root of estimated tau^2 value): 0.1880## I^2 (residual heterogeneity / unaccounted variability): 93.65%## H^2 (unaccounted variability / sampling variability): 15.74#### Test for Residual Heterogeneity:## QE(df = 109) = 1947.5929, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 240.1765, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb## factor(schizo.neurot)1 - schizo 0.2867 0.0196 14.6133 <.0001 0.2482## factor(schizo.neurot)2 - neurot 0.4987 0.0967 5.1601 <.0001 0.3093## ci.ub## factor(schizo.neurot)1 - schizo 0.3251 ***## factor(schizo.neurot)2 - neurot 0.6882 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.neurot <> Neuroticism: Reference: schizores.re.n.schizo.neurot.r <- rma(es, var, mods = ~ factor(schizo.neurot), data=dat.analysis, subset = (dat.analysis$trait == "1 - Neuroticism"))res.re.n.schizo.neurot.r

#### Mixed-Effects Model (k = 111; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0354 (SE = 0.0055)## tau (square root of estimated tau^2 value): 0.1880## I^2 (residual heterogeneity / unaccounted variability): 93.65%## H^2 (unaccounted variability / sampling variability): 15.74## R^2 (amount of heterogeneity accounted for): 4.06%#### Test for Residual Heterogeneity:## QE(df = 109) = 1947.5929, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 4.6229, p-val = 0.0315#### Model Results:#### estimate se zval pval ci.lb

22

## intrcpt 0.2867 0.0196 14.6133 <.0001 0.2482## factor(schizo.neurot)2 - neurot 0.2120 0.0986 2.1501 0.0315 0.0188## ci.ub## intrcpt 0.3251 ***## factor(schizo.neurot)2 - neurot 0.4053 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Mean corr: PP <> Extraversion ####res.re.e <- rma(es, var, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e

#### Random-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of total heterogeneity): 0.0408 (SE = 0.0065)## tau (square root of estimated tau^2 value): 0.2019## I^2 (total heterogeneity / total variability): 93.92%## H^2 (total variability / sampling variability): 16.44#### Test for Heterogeneity:## Q(df = 102) = 2225.0799, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb ci.ub## -0.0897 0.0214 -4.1927 <.0001 -0.1316 -0.0477 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1predict(res.re.e)

## pred se ci.lb ci.ub cr.lb cr.ub## -0.0897 0.0214 -0.1316 -0.0477 -0.4877 0.3084# display forest plotforest(res.re.e)

23

RE Model

−1.5 −1 −0.5 0 0.5 1

Observed Outcome

Study 349Study 346Study 343Study 341Study 339Study 338Study 333Study 332Study 328Study 324Study 323Study 319Study 316Study 313Study 309Study 307Study 304Study 301Study 298Study 295Study 292Study 289Study 286Study 283Study 280Study 277Study 274Study 271Study 268Study 259Study 256Study 253Study 250Study 247Study 244Study 241Study 238Study 235Study 232Study 229Study 223Study 222Study 219Study 218Study 215Study 214Study 210Study 206Study 197Study 194Study 191Study 188Study 168Study 165Study 162Study 159Study 155Study 152Study 150Study 147Study 144Study 141Study 138Study 135Study 132Study 127Study 124Study 121Study 118Study 115Study 112Study 109Study 106Study 103Study 97Study 95Study 93Study 86Study 83Study 80Study 77Study 74Study 71Study 68Study 66Study 64Study 62Study 60Study 57Study 54Study 51Study 48Study 45Study 42Study 39Study 36Study 33Study 30Study 27Study 24Study 8Study 5Study 2

−0.25 [−0.42, −0.07]−0.27 [−0.45, −0.09]−0.22 [−0.36, −0.07]−0.14 [−0.24, −0.05]−0.08 [−0.17, 0.02]

−0.15 [−0.27, −0.04] 0.02 [−0.08, 0.12]

−0.11 [−0.21, −0.01] 0.00 [−0.14, 0.14]

−0.08 [−0.28, 0.12]−0.28 [−0.47, −0.09]

0.03 [−0.10, 0.16]−0.41 [−0.57, −0.25]

0.25 [ 0.07, 0.43]−0.59 [−0.72, −0.46]−0.28 [−0.46, −0.10]−0.13 [−0.32, 0.06]

−0.24 [−0.44, −0.05]−0.19 [−0.24, −0.14]

0.35 [ 0.30, 0.40]−0.32 [−0.37, −0.27]

0.06 [ 0.01, 0.11]−0.17 [−0.21, −0.13]

0.36 [ 0.32, 0.40]−0.31 [−0.35, −0.27]−0.01 [−0.05, 0.03]−0.07 [−0.22, 0.08] 0.08 [−0.31, 0.47]

−0.28 [−0.54, −0.03] 0.17 [ 0.01, 0.32]

−0.23 [−0.33, −0.13]−0.50 [−0.58, −0.42]

0.02 [−0.09, 0.12]−0.14 [−0.24, −0.03]−0.08 [−0.18, 0.03]

−0.25 [−0.35, −0.16]−0.40 [−0.48, −0.31]

0.12 [ 0.02, 0.22] 0.01 [−0.10, 0.11]

−0.04 [−0.14, 0.06] 0.38 [ 0.21, 0.55]

−0.13 [−0.33, 0.07]−0.10 [−0.29, 0.09]

−0.20 [−0.31, −0.09] 0.13 [−0.06, 0.32] 0.03 [−0.09, 0.15] 0.20 [−0.07, 0.48] 0.20 [ 0.10, 0.31]

0.12 [−0.10, 0.34] 0.12 [−0.04, 0.29] 0.03 [−0.11, 0.17] 0.02 [−0.12, 0.16]

−0.36 [−0.49, −0.23]−0.40 [−0.52, −0.28]

0.03 [−0.12, 0.18]−0.07 [−0.22, 0.08]−0.12 [−0.26, 0.02] 0.06 [−0.09, 0.21] 0.04 [−0.11, 0.19]

−0.05 [−0.20, 0.10]−0.32 [−0.45, −0.19]−0.39 [−0.51, −0.27]

0.02 [−0.13, 0.17] 0.30 [ 0.17, 0.43]

−0.04 [−0.19, 0.11]−0.36 [−0.68, −0.04]−0.72 [−1.10, −0.34]

0.02 [−0.17, 0.21]−0.24 [−0.51, 0.03]−0.24 [−0.51, 0.03]−0.24 [−0.51, 0.03]−0.26 [−0.56, 0.03]−0.26 [−0.56, 0.03]−0.26 [−0.56, 0.03] 0.05 [−0.09, 0.19]

−0.49 [−0.75, −0.23]−0.14 [−0.30, 0.02]

−0.31 [−0.55, −0.07] 0.20 [ 0.00, 0.40] 0.20 [ 0.00, 0.40]

−0.01 [−0.14, 0.13]−0.14 [−0.27, −0.01]

0.03 [−0.11, 0.16] 0.03 [−0.10, 0.17]

−0.06 [−0.16, 0.05] 0.00 [−0.10, 0.10] 0.24 [ 0.14, 0.33]

0.06 [−0.04, 0.16]−0.23 [−0.30, −0.17]

0.10 [ 0.03, 0.17]−0.39 [−0.45, −0.33]

0.06 [−0.02, 0.13]−0.27 [−0.69, 0.15]

−0.16 [−0.28, −0.04] 0.10 [−0.02, 0.22]

−0.26 [−0.36, −0.16] 0.04 [−0.08, 0.16] 0.48 [ 0.40, 0.56]

−0.51 [−0.70, −0.32]−0.04 [−0.12, 0.04]

−0.23 [−0.32, −0.15]−0.16 [−0.24, −0.08]−0.30 [−0.51, −0.10]

−0.09 [−0.13, −0.05]

# display funnel plotfunnel(res.re.e)

Observed Outcome

Sta

ndar

d E

rror

0.21

30.

160.

106

0.05

30

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6

# Publication bias assessment: Regression test for funnel plot asymmetryregtest(res.re.e, model="lm")

#### Regression Test for Funnel Plot Asymmetry#### model: weighted regression with multiplicative dispersion## predictor: standard error##

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## test for funnel plot asymmetry: t = -1.0719, df = 101, p = 0.2863### Moderators: PP <> Extraversion ####

## All moderators included simultaneouslyres.re.e.metareg <- rma(es, var, mods = ~ factor(sample.clinical)

+ factor(sample.student)+ factor(schizo.measure)+ factor(posneg)+ factor(es.measure)+ factor(country.study)+ factor(language)+ factor (schizo.core)+ factor (schizo.neurot)+ year+ age.mean.all2, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))

## Warning in rma(es, var, mods = ~factor(sample.clinical) +## factor(sample.student) + : Studies with NAs omitted from model fitting.

## Warning in rma(es, var, mods = ~factor(sample.clinical) +## factor(sample.student) + : Redundant predictors dropped from the model.res.re.e.metareg

#### Mixed-Effects Model (k = 80; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0259 (SE = 0.0059)## tau (square root of estimated tau^2 value): 0.1608## I^2 (residual heterogeneity / unaccounted variability): 85.43%## H^2 (unaccounted variability / sampling variability): 6.86## R^2 (amount of heterogeneity accounted for): 40.05%#### Test for Residual Heterogeneity:## QE(df = 60) = 385.1006, p-val < .0001#### Test of Moderators (coefficient(s) 2:20):## QM(df = 19) = 60.1431, p-val < .0001#### Model Results:#### estimate## intrcpt -4.0773## factor(sample.clinical)2 - clinical 0.1707## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.1856## factor(sample.student)2 - nonstudent 0.0444## factor(sample.student)3 - combined student and nonstudent 0.0652## factor(schizo.measure)2 - rating by expert -0.0056## factor(posneg)2-negative -0.2067## factor(posneg)3-nonclassified -0.3490## factor(country.study)Australia and NZ 0.4022## factor(country.study)Continental Europe 0.1362## factor(country.study)South America 0.2972## factor(country.study)UK 0.1745## factor(country.study)USA 0.3102

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## factor(language)Non-English 0.0853## factor(schizo.core)2 - strong correlate but not core (E-) -0.1165## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.4185## factor(schizo.core)4 - neither core nor correlate -0.0165## factor(schizo.neurot)2 - neurot -0.2525## year 0.0019## age.mean.all2 -0.0000## se## intrcpt 5.4148## factor(sample.clinical)2 - clinical 0.1387## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.2089## factor(sample.student)2 - nonstudent 0.1535## factor(sample.student)3 - combined student and nonstudent 0.0888## factor(schizo.measure)2 - rating by expert 0.1093## factor(posneg)2-negative 0.0885## factor(posneg)3-nonclassified 0.1797## factor(country.study)Australia and NZ 0.2656## factor(country.study)Continental Europe 0.1202## factor(country.study)South America 0.1777## factor(country.study)UK 0.2572## factor(country.study)USA 0.2552## factor(language)Non-English 0.2425## factor(schizo.core)2 - strong correlate but not core (E-) 0.1163## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.2044## factor(schizo.core)4 - neither core nor correlate 0.1213## factor(schizo.neurot)2 - neurot 0.1137## year 0.0028## age.mean.all2 0.0094## zval## intrcpt -0.7530## factor(sample.clinical)2 - clinical 1.2307## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.8884## factor(sample.student)2 - nonstudent 0.2890## factor(sample.student)3 - combined student and nonstudent 0.7343## factor(schizo.measure)2 - rating by expert -0.0514## factor(posneg)2-negative -2.3346## factor(posneg)3-nonclassified -1.9416## factor(country.study)Australia and NZ 1.5143## factor(country.study)Continental Europe 1.1336## factor(country.study)South America 1.6726## factor(country.study)UK 0.6786## factor(country.study)USA 1.2154## factor(language)Non-English 0.3516## factor(schizo.core)2 - strong correlate but not core (E-) -1.0017## factor(schizo.core)3 - weak correlate but not core (C-, A-) 2.0474## factor(schizo.core)4 - neither core nor correlate -0.1358## factor(schizo.neurot)2 - neurot -2.2204## year 0.6829## age.mean.all2 -0.0025## pval## intrcpt 0.4515## factor(sample.clinical)2 - clinical 0.2184## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.3743## factor(sample.student)2 - nonstudent 0.7726

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## factor(sample.student)3 - combined student and nonstudent 0.4628## factor(schizo.measure)2 - rating by expert 0.9590## factor(posneg)2-negative 0.0196## factor(posneg)3-nonclassified 0.0522## factor(country.study)Australia and NZ 0.1300## factor(country.study)Continental Europe 0.2570## factor(country.study)South America 0.0944## factor(country.study)UK 0.4974## factor(country.study)USA 0.2242## factor(language)Non-English 0.7251## factor(schizo.core)2 - strong correlate but not core (E-) 0.3165## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0406## factor(schizo.core)4 - neither core nor correlate 0.8920## factor(schizo.neurot)2 - neurot 0.0264## year 0.4947## age.mean.all2 0.9980## ci.lb## intrcpt -14.6902## factor(sample.clinical)2 - clinical -0.1012## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.2238## factor(sample.student)2 - nonstudent -0.2566## factor(sample.student)3 - combined student and nonstudent -0.1088## factor(schizo.measure)2 - rating by expert -0.2199## factor(posneg)2-negative -0.3801## factor(posneg)3-nonclassified -0.7013## factor(country.study)Australia and NZ -0.1184## factor(country.study)Continental Europe -0.0993## factor(country.study)South America -0.0511## factor(country.study)UK -0.3295## factor(country.study)USA -0.1900## factor(language)Non-English -0.3900## factor(schizo.core)2 - strong correlate but not core (E-) -0.3443## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0179## factor(schizo.core)4 - neither core nor correlate -0.2543## factor(schizo.neurot)2 - neurot -0.4755## year -0.0036## age.mean.all2 -0.0185## ci.ub## intrcpt 6.5356## factor(sample.clinical)2 - clinical 0.4426## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.5950## factor(sample.student)2 - nonstudent 0.3453## factor(sample.student)3 - combined student and nonstudent 0.2392## factor(schizo.measure)2 - rating by expert 0.2087## factor(posneg)2-negative -0.0332## factor(posneg)3-nonclassified 0.0033## factor(country.study)Australia and NZ 0.9227## factor(country.study)Continental Europe 0.3717## factor(country.study)South America 0.6454## factor(country.study)UK 0.6786## factor(country.study)USA 0.8104## factor(language)Non-English 0.5605## factor(schizo.core)2 - strong correlate but not core (E-) 0.1114## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.8191

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## factor(schizo.core)4 - neither core nor correlate 0.2213## factor(schizo.neurot)2 - neurot -0.0296## year 0.0074## age.mean.all2 0.0185#### intrcpt## factor(sample.clinical)2 - clinical## factor(sample.clinical)3 - comparison of clinical and nonclinical## factor(sample.student)2 - nonstudent## factor(sample.student)3 - combined student and nonstudent## factor(schizo.measure)2 - rating by expert## factor(posneg)2-negative *## factor(posneg)3-nonclassified .## factor(country.study)Australia and NZ## factor(country.study)Continental Europe## factor(country.study)South America .## factor(country.study)UK## factor(country.study)USA## factor(language)Non-English## factor(schizo.core)2 - strong correlate but not core (E-)## factor(schizo.core)3 - weak correlate but not core (C-, A-) *## factor(schizo.core)4 - neither core nor correlate## factor(schizo.neurot)2 - neurot *## year## age.mean.all2#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.clinical <> Extraversionres.re.e.sample.clinical <- rma(es, var, mods = ~ factor(sample.clinical)-1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.sample.clinical

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0392 (SE = 0.0064)## tau (square root of estimated tau^2 value): 0.1980## I^2 (residual heterogeneity / unaccounted variability): 93.70%## H^2 (unaccounted variability / sampling variability): 15.87#### Test for Residual Heterogeneity:## QE(df = 100) = 2174.5989, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 24.1246, p-val < .0001#### Model Results:#### estimate## factor(sample.clinical)1 - nonclinical -0.0781## factor(sample.clinical)2 - clinical 0.0157## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.1961## se## factor(sample.clinical)1 - nonclinical 0.0239

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## factor(sample.clinical)2 - clinical 0.0783## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0536## zval## factor(sample.clinical)1 - nonclinical -3.2689## factor(sample.clinical)2 - clinical 0.2005## factor(sample.clinical)3 - comparison of clinical and nonclinical -3.6604## pval## factor(sample.clinical)1 - nonclinical 0.0011## factor(sample.clinical)2 - clinical 0.8411## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0003## ci.lb## factor(sample.clinical)1 - nonclinical -0.1249## factor(sample.clinical)2 - clinical -0.1378## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.3011## ci.ub## factor(sample.clinical)1 - nonclinical -0.0313## factor(sample.clinical)2 - clinical 0.1692## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.0911#### factor(sample.clinical)1 - nonclinical **## factor(sample.clinical)2 - clinical## factor(sample.clinical)3 - comparison of clinical and nonclinical ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.clinical <> Extraversion: Reference: nonclinicalres.re.e.sample.clinical.r <- rma(es, var, mods = ~ factor(sample.clinical), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.sample.clinical.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0392 (SE = 0.0064)## tau (square root of estimated tau^2 value): 0.1980## I^2 (residual heterogeneity / unaccounted variability): 93.70%## H^2 (unaccounted variability / sampling variability): 15.87## R^2 (amount of heterogeneity accounted for): 3.88%#### Test for Residual Heterogeneity:## QE(df = 100) = 2174.5989, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 5.9937, p-val = 0.0499#### Model Results:#### estimate## intrcpt -0.0781## factor(sample.clinical)2 - clinical 0.0938## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.1180## se## intrcpt 0.0239## factor(sample.clinical)2 - clinical 0.0819## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0587

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## zval## intrcpt -3.2689## factor(sample.clinical)2 - clinical 1.1456## factor(sample.clinical)3 - comparison of clinical and nonclinical -2.0122## pval## intrcpt 0.0011## factor(sample.clinical)2 - clinical 0.2520## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0442## ci.lb## intrcpt -0.1249## factor(sample.clinical)2 - clinical -0.0667## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.2330## ci.ub## intrcpt -0.0313## factor(sample.clinical)2 - clinical 0.2542## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.0031#### intrcpt **## factor(sample.clinical)2 - clinical## factor(sample.clinical)3 - comparison of clinical and nonclinical *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.student <> Extraversionres.re.e.sample.student <- rma(es, var, mods = ~ factor(sample.student) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.sample.student

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0412 (SE = 0.0067)## tau (square root of estimated tau^2 value): 0.2029## I^2 (residual heterogeneity / unaccounted variability): 93.90%## H^2 (unaccounted variability / sampling variability): 16.39#### Test for Residual Heterogeneity:## QE(df = 100) = 2179.3042, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 18.4611, p-val = 0.0004#### Model Results:#### estimate## factor(sample.student)1 - student -0.0902## factor(sample.student)2 - nonstudent -0.0712## factor(sample.student)3 - combined student and nonstudent -0.1326## se zval## factor(sample.student)1 - student 0.0338 -2.6709## factor(sample.student)2 - nonstudent 0.0332 -2.1453## factor(sample.student)3 - combined student and nonstudent 0.0511 -2.5933## pval ci.lb## factor(sample.student)1 - student 0.0076 -0.1564## factor(sample.student)2 - nonstudent 0.0319 -0.1362

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## factor(sample.student)3 - combined student and nonstudent 0.0095 -0.2328## ci.ub## factor(sample.student)1 - student -0.0240 **## factor(sample.student)2 - nonstudent -0.0061 *## factor(sample.student)3 - combined student and nonstudent -0.0324 **#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.student <> Extraversion: Reference: studentres.re.e.sample.student.r <- rma(es, var, mods = ~ factor(sample.student), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.sample.student.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0412 (SE = 0.0067)## tau (square root of estimated tau^2 value): 0.2029## I^2 (residual heterogeneity / unaccounted variability): 93.90%## H^2 (unaccounted variability / sampling variability): 16.39## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 100) = 2179.3042, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 1.0172, p-val = 0.6013#### Model Results:#### estimate## intrcpt -0.0902## factor(sample.student)2 - nonstudent 0.0190## factor(sample.student)3 - combined student and nonstudent -0.0424## se zval## intrcpt 0.0338 -2.6709## factor(sample.student)2 - nonstudent 0.0473 0.4024## factor(sample.student)3 - combined student and nonstudent 0.0613 -0.6921## pval ci.lb## intrcpt 0.0076 -0.1564## factor(sample.student)2 - nonstudent 0.6874 -0.0737## factor(sample.student)3 - combined student and nonstudent 0.4889 -0.1625## ci.ub## intrcpt -0.0240 **## factor(sample.student)2 - nonstudent 0.1118## factor(sample.student)3 - combined student and nonstudent 0.0777#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.measure <> Extraversionres.re.e.schizo.measure <- rma(es, var, mods = ~ factor(schizo.measure) -1,data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.schizo.measure

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)

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#### tau^2 (estimated amount of residual heterogeneity): 0.0409 (SE = 0.0066)## tau (square root of estimated tau^2 value): 0.2022## I^2 (residual heterogeneity / unaccounted variability): 93.92%## H^2 (unaccounted variability / sampling variability): 16.45#### Test for Residual Heterogeneity:## QE(df = 101) = 2208.4275, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 18.6501, p-val < .0001#### Model Results:#### estimate se zval## factor(schizo.measure)1 - self-report -0.0815 0.0228 -3.5747## factor(schizo.measure)2 - rating by expert -0.1516 0.0626 -2.4231## pval ci.lb ci.ub## factor(schizo.measure)1 - self-report 0.0004 -0.1261 -0.0368 ***## factor(schizo.measure)2 - rating by expert 0.0154 -0.2742 -0.0290 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.measure <> Extraversion: Reference: self-reportres.re.e.schizo.measure.r <- rma(es, var, mods = ~ factor(schizo.measure),data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.schizo.measure.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0409 (SE = 0.0066)## tau (square root of estimated tau^2 value): 0.2022## I^2 (residual heterogeneity / unaccounted variability): 93.92%## H^2 (unaccounted variability / sampling variability): 16.45## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 101) = 2208.4275, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 1.1098, p-val = 0.2921#### Model Results:#### estimate se zval## intrcpt -0.0815 0.0228 -3.5747## factor(schizo.measure)2 - rating by expert -0.0701 0.0666 -1.0535## pval ci.lb ci.ub## intrcpt 0.0004 -0.1261 -0.0368 ***## factor(schizo.measure)2 - rating by expert 0.2921 -0.2006 0.0604#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

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## posneg <> Extraversionres.re.e.posneg <- rma(es, var, mods = ~ factor(posneg) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.posneg

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0343 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1851## I^2 (residual heterogeneity / unaccounted variability): 92.57%## H^2 (unaccounted variability / sampling variability): 13.46#### Test for Residual Heterogeneity:## QE(df = 100) = 1366.0730, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 36.5570, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb## factor(posneg)1-positive -0.0190 0.0277 -0.6855 0.4930 -0.0734## factor(posneg)2-negative -0.2116 0.0389 -5.4353 <.0001 -0.2879## factor(posneg)3-nonclassified -0.1059 0.0414 -2.5583 0.0105 -0.1869## ci.ub## factor(posneg)1-positive 0.0353## factor(posneg)2-negative -0.1353 ***## factor(posneg)3-nonclassified -0.0248 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## posneg <> Extraversion: Reference: positiveres.re.e.posneg.r <- rma(es, var, mods = ~ factor(posneg), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.posneg.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0343 (SE = 0.0057)## tau (square root of estimated tau^2 value): 0.1851## I^2 (residual heterogeneity / unaccounted variability): 92.57%## H^2 (unaccounted variability / sampling variability): 13.46## R^2 (amount of heterogeneity accounted for): 15.94%#### Test for Residual Heterogeneity:## QE(df = 100) = 1366.0730, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 16.4514, p-val = 0.0003#### Model Results:#### estimate se zval pval ci.lb## intrcpt -0.0190 0.0277 -0.6855 0.4930 -0.0734

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## factor(posneg)2-negative -0.1926 0.0478 -4.0291 <.0001 -0.2862## factor(posneg)3-nonclassified -0.0868 0.0498 -1.7435 0.0812 -0.1845## ci.ub## intrcpt 0.0353## factor(posneg)2-negative -0.0989 ***## factor(posneg)3-nonclassified 0.0108 .#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## es.measure <> Extraversionres.re.e.es.measure <- rma(es, var, mods = ~ factor(es.measure) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.es.measure

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0389 (SE = 0.0063)## tau (square root of estimated tau^2 value): 0.1972## I^2 (residual heterogeneity / unaccounted variability): 93.63%## H^2 (unaccounted variability / sampling variability): 15.70#### Test for Residual Heterogeneity:## QE(df = 101) = 2175.2239, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 24.5492, p-val < .0001#### Model Results:#### estimate se zval pval## factor(es.measure)1 - correlation -0.0677 0.0227 -2.9854 0.0028## factor(es.measure)2 - Cohen's d -0.2165 0.0548 -3.9543 <.0001## ci.lb ci.ub## factor(es.measure)1 - correlation -0.1121 -0.0232 **## factor(es.measure)2 - Cohen's d -0.3239 -0.1092 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## es.measure <> Extraversion: Reference: correlationres.re.e.es.measure.r <- rma(es, var, mods = ~ factor(es.measure), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.es.measure.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0389 (SE = 0.0063)## tau (square root of estimated tau^2 value): 0.1972## I^2 (residual heterogeneity / unaccounted variability): 93.63%## H^2 (unaccounted variability / sampling variability): 15.70## R^2 (amount of heterogeneity accounted for): 4.62%#### Test for Residual Heterogeneity:## QE(df = 101) = 2175.2239, p-val < .0001##

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## Test of Moderators (coefficient(s) 2):## QM(df = 1) = 6.3088, p-val = 0.0120#### Model Results:#### estimate se zval pval## intrcpt -0.0677 0.0227 -2.9854 0.0028## factor(es.measure)2 - Cohen's d -0.1489 0.0593 -2.5117 0.0120## ci.lb ci.ub## intrcpt -0.1121 -0.0232 **## factor(es.measure)2 - Cohen's d -0.2650 -0.0327 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## country.study <> Extraversionres.re.e.country.study <- rma(es, var, mods = ~ factor(country.study) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.country.study

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0371 (SE = 0.0062)## tau (square root of estimated tau^2 value): 0.1926## I^2 (residual heterogeneity / unaccounted variability): 93.21%## H^2 (unaccounted variability / sampling variability): 14.73#### Test for Residual Heterogeneity:## QE(df = 96) = 1983.6243, p-val < .0001#### Test of Moderators (coefficient(s) 1:7):## QM(df = 7) = 34.4241, p-val < .0001#### Model Results:#### estimate se zval pval## factor(country.study)Asia -0.2752 0.1196 -2.3008 0.0214## factor(country.study)Australia and NZ 0.0081 0.0575 0.1406 0.8881## factor(country.study)Continental Europe -0.1403 0.0392 -3.5759 0.0003## factor(country.study)Israel 0.2030 0.2380 0.8529 0.3937## factor(country.study)South America 0.0129 0.0671 0.1916 0.8480## factor(country.study)UK -0.1335 0.0340 -3.9309 <.0001## factor(country.study)USA 0.0208 0.0635 0.3269 0.7437## ci.lb ci.ub## factor(country.study)Asia -0.5096 -0.0408 *## factor(country.study)Australia and NZ -0.1046 0.1208## factor(country.study)Continental Europe -0.2172 -0.0634 ***## factor(country.study)Israel -0.2635 0.6695## factor(country.study)South America -0.1187 0.1444## factor(country.study)UK -0.2001 -0.0670 ***## factor(country.study)USA -0.1037 0.1452#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

35

## country.study <> Extraversion: Reference: Asiares.re.e.country.study.r <- rma(es, var, mods = ~ factor(country.study), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.country.study.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0371 (SE = 0.0062)## tau (square root of estimated tau^2 value): 0.1926## I^2 (residual heterogeneity / unaccounted variability): 93.21%## H^2 (unaccounted variability / sampling variability): 14.73## R^2 (amount of heterogeneity accounted for): 9.06%#### Test for Residual Heterogeneity:## QE(df = 96) = 1983.6243, p-val < .0001#### Test of Moderators (coefficient(s) 2:7):## QM(df = 6) = 15.4979, p-val = 0.0167#### Model Results:#### estimate se zval pval## intrcpt -0.2752 0.1196 -2.3008 0.0214## factor(country.study)Australia and NZ 0.2833 0.1327 2.1346 0.0328## factor(country.study)Continental Europe 0.1349 0.1259 1.0717 0.2839## factor(country.study)Israel 0.4782 0.2664 1.7952 0.0726## factor(country.study)South America 0.2880 0.1371 2.1002 0.0357## factor(country.study)UK 0.1416 0.1243 1.1393 0.2546## factor(country.study)USA 0.2959 0.1354 2.1854 0.0289## ci.lb ci.ub## intrcpt -0.5096 -0.0408 *## factor(country.study)Australia and NZ 0.0232 0.5433 *## factor(country.study)Continental Europe -0.1118 0.3816## factor(country.study)Israel -0.0439 1.0002 .## factor(country.study)South America 0.0192 0.5568 *## factor(country.study)UK -0.1020 0.3853## factor(country.study)USA 0.0305 0.5613 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## language <> Extraversionres.re.e.language <- rma(es, var, mods = ~ factor(language) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.language

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0412 (SE = 0.0066)## tau (square root of estimated tau^2 value): 0.2029## I^2 (residual heterogeneity / unaccounted variability): 93.90%## H^2 (unaccounted variability / sampling variability): 16.40#### Test for Residual Heterogeneity:## QE(df = 101) = 2177.7523, p-val < .0001

36

#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 17.6425, p-val = 0.0001#### Model Results:#### estimate se zval pval ci.lb## factor(language)English -0.0818 0.0280 -2.9162 0.0035 -0.1367## factor(language)Non-English -0.1009 0.0334 -3.0230 0.0025 -0.1664## ci.ub## factor(language)English -0.0268 **## factor(language)Non-English -0.0355 **#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## language <> Extraversion: Reference: Englishres.re.e.language.r <- rma(es, var, mods = ~ factor(language), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.language.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0412 (SE = 0.0066)## tau (square root of estimated tau^2 value): 0.2029## I^2 (residual heterogeneity / unaccounted variability): 93.90%## H^2 (unaccounted variability / sampling variability): 16.40## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 101) = 2177.7523, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.1928, p-val = 0.6606#### Model Results:#### estimate se zval pval ci.lb## intrcpt -0.0818 0.0280 -2.9162 0.0035 -0.1367## factor(language)Non-English -0.0191 0.0436 -0.4391 0.6606 -0.1046## ci.ub## intrcpt -0.0268 **## factor(language)Non-English 0.0663#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## year <> Extraversionres.re.e.year <- rma(es, var, mods = ~ year, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.year

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0391 (SE = 0.0063)## tau (square root of estimated tau^2 value): 0.1976

37

## I^2 (residual heterogeneity / unaccounted variability): 93.65%## H^2 (unaccounted variability / sampling variability): 15.74## R^2 (amount of heterogeneity accounted for): 4.21%#### Test for Residual Heterogeneity:## QE(df = 101) = 2174.5922, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 5.6226, p-val = 0.0177#### Model Results:#### estimate se zval pval ci.lb ci.ub## intrcpt -8.3956 3.5030 -2.3967 0.0165 -15.2612 -1.5299 *## year 0.0042 0.0018 2.3712 0.0177 0.0007 0.0076 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## age.mean.all2 <> Extraversionres.re.e.age.mean.all2 <- rma(es, var, mods = ~ age.mean.all2, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))

## Warning in rma(es, var, mods = ~age.mean.all2, data = dat.analysis, subset## = (dat.analysis$trait == : Studies with NAs omitted from model fitting.res.re.e.age.mean.all2

#### Mixed-Effects Model (k = 80; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0438 (SE = 0.0081)## tau (square root of estimated tau^2 value): 0.2092## I^2 (residual heterogeneity / unaccounted variability): 91.79%## H^2 (unaccounted variability / sampling variability): 12.18## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 78) = 1012.6830, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.0000, p-val = 0.9996#### Model Results:#### estimate se zval pval ci.lb ci.ub## intrcpt -0.1084 0.1069 -1.0140 0.3106 -0.3178 0.1011## age.mean.all2 0.0000 0.0039 0.0005 0.9996 -0.0077 0.0077#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.core <> Extraversionres.re.e.schizo.core <- rma(es, var, mods = ~ factor(schizo.core) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.schizo.core

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)

38

#### tau^2 (estimated amount of residual heterogeneity): 0.0310 (SE = 0.0052)## tau (square root of estimated tau^2 value): 0.1760## I^2 (residual heterogeneity / unaccounted variability): 91.46%## H^2 (unaccounted variability / sampling variability): 11.71#### Test for Residual Heterogeneity:## QE(df = 99) = 921.0466, p-val < .0001#### Test of Moderators (coefficient(s) 1:4):## QM(df = 4) = 48.7711, p-val < .0001#### Model Results:#### estimate## factor(schizo.core)1 - core schizotypy content -0.0735## factor(schizo.core)2 - strong correlate but not core (E-) -0.2950## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.1494## factor(schizo.core)4 - neither core nor correlate -0.2251## se## factor(schizo.core)1 - core schizotypy content 0.0217## factor(schizo.core)2 - strong correlate but not core (E-) 0.0608## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0696## factor(schizo.core)4 - neither core nor correlate 0.0744## zval## factor(schizo.core)1 - core schizotypy content -3.3828## factor(schizo.core)2 - strong correlate but not core (E-) -4.8549## factor(schizo.core)3 - weak correlate but not core (C-, A-) 2.1453## factor(schizo.core)4 - neither core nor correlate -3.0258## pval## factor(schizo.core)1 - core schizotypy content 0.0007## factor(schizo.core)2 - strong correlate but not core (E-) <.0001## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0319## factor(schizo.core)4 - neither core nor correlate 0.0025## ci.lb## factor(schizo.core)1 - core schizotypy content -0.1161## factor(schizo.core)2 - strong correlate but not core (E-) -0.4141## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0129## factor(schizo.core)4 - neither core nor correlate -0.3710## ci.ub## factor(schizo.core)1 - core schizotypy content -0.0309 ***## factor(schizo.core)2 - strong correlate but not core (E-) -0.1759 ***## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.2859 *## factor(schizo.core)4 - neither core nor correlate -0.0793 **#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.core <> Extraversion: Reference: core schizotypy contentres.re.e.schizo.core.r <- rma(es, var, mods = ~ factor(schizo.core), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.schizo.core.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)##

39

## tau^2 (estimated amount of residual heterogeneity): 0.0310 (SE = 0.0052)## tau (square root of estimated tau^2 value): 0.1760## I^2 (residual heterogeneity / unaccounted variability): 91.46%## H^2 (unaccounted variability / sampling variability): 11.71## R^2 (amount of heterogeneity accounted for): 24.02%#### Test for Residual Heterogeneity:## QE(df = 99) = 921.0466, p-val < .0001#### Test of Moderators (coefficient(s) 2:4):## QM(df = 3) = 27.0695, p-val < .0001#### Model Results:#### estimate## intrcpt -0.0735## factor(schizo.core)2 - strong correlate but not core (E-) -0.2215## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.2229## factor(schizo.core)4 - neither core nor correlate -0.1516## se## intrcpt 0.0217## factor(schizo.core)2 - strong correlate but not core (E-) 0.0645## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0729## factor(schizo.core)4 - neither core nor correlate 0.0775## zval## intrcpt -3.3828## factor(schizo.core)2 - strong correlate but not core (E-) -3.4324## factor(schizo.core)3 - weak correlate but not core (C-, A-) 3.0557## factor(schizo.core)4 - neither core nor correlate -1.9561## pval## intrcpt 0.0007## factor(schizo.core)2 - strong correlate but not core (E-) 0.0006## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0022## factor(schizo.core)4 - neither core nor correlate 0.0505## ci.lb## intrcpt -0.1161## factor(schizo.core)2 - strong correlate but not core (E-) -0.3480## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0799## factor(schizo.core)4 - neither core nor correlate -0.3036## ci.ub## intrcpt -0.0309 ***## factor(schizo.core)2 - strong correlate but not core (E-) -0.0950 ***## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.3659 **## factor(schizo.core)4 - neither core nor correlate 0.0003 .#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.neurot <> Extraversionres.re.e.schizo.neurot <- rma(es, var, mods = ~ factor(schizo.neurot) -1, data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.schizo.neurot

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)##

40

## tau^2 (estimated amount of residual heterogeneity): 0.0409 (SE = 0.0066)## tau (square root of estimated tau^2 value): 0.2023## I^2 (residual heterogeneity / unaccounted variability): 93.90%## H^2 (unaccounted variability / sampling variability): 16.39#### Test for Residual Heterogeneity:## QE(df = 101) = 2203.5374, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 18.1975, p-val = 0.0001#### Model Results:#### estimate se zval pval## factor(schizo.neurot)1 - schizo -0.0861 0.0219 -3.9351 <.0001## factor(schizo.neurot)2 - neurot -0.1742 0.1058 -1.6471 0.0995## ci.lb ci.ub## factor(schizo.neurot)1 - schizo -0.1289 -0.0432 ***## factor(schizo.neurot)2 - neurot -0.3815 0.0331 .#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.neurot <> Extraversion: Reference: schizores.re.e.schizo.neurot.r <- rma(es, var, mods = ~ factor(schizo.neurot), data=dat.analysis, subset = (dat.analysis$trait == "2 - Extraversion"))res.re.e.schizo.neurot.r

#### Mixed-Effects Model (k = 103; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0409 (SE = 0.0066)## tau (square root of estimated tau^2 value): 0.2023## I^2 (residual heterogeneity / unaccounted variability): 93.90%## H^2 (unaccounted variability / sampling variability): 16.39## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 101) = 2203.5374, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.6662, p-val = 0.4144#### Model Results:#### estimate se zval pval## intrcpt -0.0861 0.0219 -3.9351 <.0001## factor(schizo.neurot)2 - neurot -0.0882 0.1080 -0.8162 0.4144## ci.lb ci.ub## intrcpt -0.1289 -0.0432 ***## factor(schizo.neurot)2 - neurot -0.2999 0.1235#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

41

# Mean corr: PP <> Psychoticism ####res.re.p <- rma(es, var, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p

#### Random-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of total heterogeneity): 0.0217 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1474## I^2 (total heterogeneity / total variability): 88.85%## H^2 (total variability / sampling variability): 8.97#### Test for Heterogeneity:## Q(df = 135) = 1934.7584, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb ci.ub## 0.2084 0.0145 14.4033 <.0001 0.1801 0.2368 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1predict(res.re.p)

## pred se ci.lb ci.ub cr.lb cr.ub## 0.2084 0.0145 0.1801 0.2368 -0.0818 0.4987# display forest plotforest(res.re.p)

RE Model

−1 −0.5 0 0.5 1

Observed Outcome

Study 350Study 347Study 344Study 335Study 334Study 329Study 326Study 325Study 320Study 317Study 314Study 311Study 308Study 305Study 302Study 299Study 296Study 293Study 290Study 287Study 284Study 281Study 278Study 275Study 272Study 269Study 266Study 265Study 264Study 263Study 262Study 261Study 260Study 257Study 254Study 251Study 248Study 245Study 242Study 239Study 236Study 233Study 230Study 227Study 226Study 225Study 224Study 211Study 208Study 205Study 203Study 201Study 199Study 195Study 192Study 189Study 186Study 184Study 182Study 180Study 179Study 178Study 177Study 176Study 175Study 174Study 173Study 172Study 171Study 170Study 169Study 166Study 163Study 160Study 157Study 154Study 151Study 148Study 145Study 142Study 139Study 136Study 133Study 130Study 129Study 128Study 125Study 122Study 119Study 116Study 113Study 110Study 107Study 104Study 101Study 100Study 98Study 91Study 90Study 89Study 88Study 87Study 84Study 81Study 78Study 75Study 72Study 69Study 58Study 55Study 52Study 49Study 46Study 43Study 40Study 37Study 34Study 31Study 28Study 25Study 22Study 21Study 20Study 19Study 18Study 17Study 16Study 15Study 14Study 13Study 12Study 11Study 10Study 9Study 6Study 3

0.35 [ 0.17, 0.53] 0.30 [ 0.12, 0.48]

0.06 [−0.08, 0.20] 0.11 [ 0.01, 0.21]

0.08 [−0.02, 0.18] 0.01 [−0.13, 0.15] 0.13 [−0.07, 0.33] 0.07 [−0.13, 0.27] 0.53 [ 0.44, 0.62]

0.07 [−0.13, 0.27] 0.55 [ 0.41, 0.69] 0.26 [ 0.08, 0.44]

0.14 [−0.05, 0.33] 0.23 [ 0.04, 0.42] 0.31 [ 0.11, 0.50]

−0.01 [−0.06, 0.04] 0.27 [ 0.22, 0.32] 0.12 [ 0.07, 0.17] 0.08 [ 0.03, 0.13]

−0.01 [−0.05, 0.03] 0.30 [ 0.26, 0.34] 0.07 [ 0.03, 0.11] 0.15 [ 0.11, 0.19] 0.28 [ 0.14, 0.42] 0.43 [ 0.11, 0.75]

0.14 [−0.11, 0.39] 0.14 [−0.14, 0.42] 0.15 [−0.13, 0.43] 0.13 [−0.01, 0.27] 0.37 [ 0.25, 0.49] 0.23 [ 0.10, 0.36]

0.13 [−0.01, 0.27] 0.28 [ 0.14, 0.43] 0.15 [ 0.05, 0.25] 0.21 [ 0.11, 0.31] 0.20 [ 0.10, 0.30] 0.23 [ 0.13, 0.33] 0.22 [ 0.13, 0.32] 0.11 [ 0.01, 0.21] 0.31 [ 0.22, 0.40] 0.23 [ 0.14, 0.33] 0.25 [ 0.16, 0.35] 0.35 [ 0.26, 0.44] 0.41 [ 0.04, 0.78] 0.31 [ 0.05, 0.57] 0.38 [ 0.21, 0.55] 0.33 [ 0.15, 0.51]

0.21 [−0.06, 0.48] 0.19 [ 0.08, 0.29] 0.28 [ 0.11, 0.45]

0.13 [−0.05, 0.31] 0.32 [ 0.16, 0.48] 0.26 [ 0.09, 0.43]

0.10 [−0.07, 0.27] 0.13 [−0.00, 0.26] 0.29 [ 0.17, 0.41] 0.25 [ 0.12, 0.38] 0.24 [ 0.11, 0.37] 0.16 [ 0.03, 0.29]

0.05 [−0.02, 0.12] 0.67 [ 0.63, 0.71] 0.32 [ 0.26, 0.38] 0.34 [ 0.28, 0.40]

0.01 [−0.07, 0.09] 0.68 [ 0.64, 0.72] 0.32 [ 0.25, 0.39] 0.33 [ 0.26, 0.40] 0.23 [ 0.12, 0.34]

−0.01 [−0.12, 0.10] 0.28 [ 0.17, 0.39]

−0.02 [−0.17, 0.13] 0.15 [ 0.01, 0.29] 0.34 [ 0.21, 0.47] 0.25 [ 0.11, 0.39] 0.17 [ 0.03, 0.31] 0.31 [ 0.18, 0.44] 0.34 [ 0.21, 0.47] 0.30 [ 0.17, 0.43]

0.01 [−0.14, 0.16] 0.06 [−0.09, 0.21] 0.28 [ 0.14, 0.42] 0.49 [ 0.38, 0.60] 0.25 [ 0.11, 0.39]

0.22 [−0.04, 0.48] 0.11 [−0.16, 0.38] 0.18 [−0.13, 0.49]

−0.19 [−0.50, 0.11]−0.13 [−0.32, 0.06]

−0.40 [−0.64, −0.16]−0.19 [−0.46, 0.09]

−0.29 [−0.56, −0.03]−0.19 [−0.49, 0.11]−0.00 [−0.32, 0.31]−0.11 [−0.42, 0.20] 0.22 [−0.04, 0.48] 0.26 [ 0.16, 0.36] 0.43 [ 0.31, 0.55]

0.12 [−0.10, 0.34] 0.09 [−0.14, 0.32] 0.00 [−0.29, 0.29]

−0.04 [−0.33, 0.25] 0.26 [ 0.03, 0.50] 0.31 [ 0.13, 0.49] 0.35 [ 0.17, 0.53] 0.16 [ 0.03, 0.29] 0.20 [ 0.07, 0.33] 0.13 [ 0.00, 0.27]

0.06 [−0.08, 0.19] 0.06 [−0.01, 0.13] 0.31 [ 0.24, 0.37]

0.06 [−0.01, 0.13] 0.16 [ 0.09, 0.23] 0.40 [ 0.02, 0.78] 0.26 [ 0.15, 0.37] 0.52 [ 0.43, 0.61] 0.17 [ 0.06, 0.28] 0.25 [ 0.14, 0.36] 0.30 [ 0.20, 0.40]

−0.23 [−0.48, 0.02] 0.12 [ 0.04, 0.20] 0.32 [ 0.03, 0.61] 0.29 [ 0.08, 0.50] 0.36 [ 0.16, 0.56]

0.15 [−0.16, 0.46] 0.18 [−0.04, 0.40]

−0.09 [−0.41, 0.23] 0.33 [ 0.13, 0.53]

−0.05 [−0.37, 0.27] 0.32 [ 0.12, 0.52]

0.14 [−0.18, 0.46] 0.27 [ 0.12, 0.42] 0.37 [ 0.23, 0.51]

0.22 [−0.10, 0.54] 0.39 [ 0.30, 0.47] 0.33 [ 0.25, 0.41] 0.60 [ 0.37, 0.82]

0.21 [ 0.18, 0.24]

# display funnel plotfunnel(res.re.p)

42

Observed Outcome

Sta

ndar

d E

rror

0.19

30.

145

0.09

60.

048

0

−0.4 −0.2 0 0.2 0.4 0.6 0.8

# Publication bias assessment: Regression test for funnel plot asymmetryregtest(res.re.p, model="lm")

#### Regression Test for Funnel Plot Asymmetry#### model: weighted regression with multiplicative dispersion## predictor: standard error#### test for funnel plot asymmetry: t = -2.1416, df = 134, p = 0.0340# Moderators: PP <> Psychoticism ####

## All moderators included simultaneouslyres.re.p.metareg <- rma(es, var, mods = ~ factor(sample.clinical)

+ factor(sample.student)+ factor(schizo.measure)+ factor(posneg)+ factor(es.measure)+ factor(country.study)+ factor(language)+ factor (schizo.core)+ factor (schizo.neurot)+ year+ age.mean.all2, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))

## Warning in rma(es, var, mods = ~factor(sample.clinical) +## factor(sample.student) + : Studies with NAs omitted from model fitting.

## Warning in rma(es, var, mods = ~factor(sample.clinical) +## factor(sample.student) + : Redundant predictors dropped from the model.res.re.p.metareg

##

43

## Mixed-Effects Model (k = 105; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0150 (SE = 0.0035)## tau (square root of estimated tau^2 value): 0.1226## I^2 (residual heterogeneity / unaccounted variability): 73.45%## H^2 (unaccounted variability / sampling variability): 3.77## R^2 (amount of heterogeneity accounted for): 15.85%#### Test for Residual Heterogeneity:## QE(df = 84) = 279.7402, p-val < .0001#### Test of Moderators (coefficient(s) 2:21):## QM(df = 20) = 36.6464, p-val = 0.0129#### Model Results:#### estimate## intrcpt -0.8507## factor(sample.clinical)2 - clinical 0.0577## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.1723## factor(sample.student)2 - nonstudent 0.0514## factor(sample.student)3 - combined student and nonstudent 0.1341## factor(schizo.measure)2 - rating by expert -0.0147## factor(posneg)2-negative -0.1111## factor(posneg)3-nonclassified -0.1778## factor(country.study)Australia and NZ -0.0284## factor(country.study)Continental Europe -0.1261## factor(country.study)Israel 0.0477## factor(country.study)South America -0.1795## factor(country.study)UK -0.2106## factor(country.study)USA -0.0774## factor(language)Non-English -0.0110## factor(schizo.core)2 - strong correlate but not core (E-) 0.1478## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.4354## factor(schizo.core)4 - neither core nor correlate 0.0692## factor(schizo.neurot)2 - neurot -0.0748## year 0.0005## age.mean.all2 0.0053## se## intrcpt 3.8437## factor(sample.clinical)2 - clinical 0.1080## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.1690## factor(sample.student)2 - nonstudent 0.0707## factor(sample.student)3 - combined student and nonstudent 0.0562## factor(schizo.measure)2 - rating by expert 0.0855## factor(posneg)2-negative 0.0691## factor(posneg)3-nonclassified 0.1483## factor(country.study)Australia and NZ 0.1596## factor(country.study)Continental Europe 0.1205## factor(country.study)Israel 0.2037## factor(country.study)South America 0.1829## factor(country.study)UK 0.1461## factor(country.study)USA 0.1408## factor(language)Non-English 0.0812

44

## factor(schizo.core)2 - strong correlate but not core (E-) 0.0844## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.1669## factor(schizo.core)4 - neither core nor correlate 0.0922## factor(schizo.neurot)2 - neurot 0.0924## year 0.0019## age.mean.all2 0.0052## zval## intrcpt -0.2213## factor(sample.clinical)2 - clinical 0.5347## factor(sample.clinical)3 - comparison of clinical and nonclinical 1.0193## factor(sample.student)2 - nonstudent 0.7260## factor(sample.student)3 - combined student and nonstudent 2.3880## factor(schizo.measure)2 - rating by expert -0.1724## factor(posneg)2-negative -1.6077## factor(posneg)3-nonclassified -1.1989## factor(country.study)Australia and NZ -0.1778## factor(country.study)Continental Europe -1.0463## factor(country.study)Israel 0.2343## factor(country.study)South America -0.9813## factor(country.study)UK -1.4412## factor(country.study)USA -0.5498## factor(language)Non-English -0.1358## factor(schizo.core)2 - strong correlate but not core (E-) 1.7516## factor(schizo.core)3 - weak correlate but not core (C-, A-) 2.6085## factor(schizo.core)4 - neither core nor correlate 0.7509## factor(schizo.neurot)2 - neurot -0.8089## year 0.2657## age.mean.all2 1.0193## pval## intrcpt 0.8248## factor(sample.clinical)2 - clinical 0.5929## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.3081## factor(sample.student)2 - nonstudent 0.4678## factor(sample.student)3 - combined student and nonstudent 0.0169## factor(schizo.measure)2 - rating by expert 0.8631## factor(posneg)2-negative 0.1079## factor(posneg)3-nonclassified 0.2306## factor(country.study)Australia and NZ 0.8589## factor(country.study)Continental Europe 0.2954## factor(country.study)Israel 0.8147## factor(country.study)South America 0.3264## factor(country.study)UK 0.1495## factor(country.study)USA 0.5825## factor(language)Non-English 0.8920## factor(schizo.core)2 - strong correlate but not core (E-) 0.0799## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0091## factor(schizo.core)4 - neither core nor correlate 0.4527## factor(schizo.neurot)2 - neurot 0.4186## year 0.7905## age.mean.all2 0.3080## ci.lb## intrcpt -8.3842## factor(sample.clinical)2 - clinical -0.1539## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.1590

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## factor(sample.student)2 - nonstudent -0.0873## factor(sample.student)3 - combined student and nonstudent 0.0240## factor(schizo.measure)2 - rating by expert -0.1823## factor(posneg)2-negative -0.2466## factor(posneg)3-nonclassified -0.4684## factor(country.study)Australia and NZ -0.3411## factor(country.study)Continental Europe -0.3624## factor(country.study)Israel -0.3516## factor(country.study)South America -0.5380## factor(country.study)UK -0.4970## factor(country.study)USA -0.3534## factor(language)Non-English -0.1701## factor(schizo.core)2 - strong correlate but not core (E-) -0.0176## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.1083## factor(schizo.core)4 - neither core nor correlate -0.1115## factor(schizo.neurot)2 - neurot -0.2559## year -0.0033## age.mean.all2 -0.0049## ci.ub## intrcpt 6.6828## factor(sample.clinical)2 - clinical 0.2693## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.5035## factor(sample.student)2 - nonstudent 0.1900## factor(sample.student)3 - combined student and nonstudent 0.2441## factor(schizo.measure)2 - rating by expert 0.1528## factor(posneg)2-negative 0.0243## factor(posneg)3-nonclassified 0.1128## factor(country.study)Australia and NZ 0.2844## factor(country.study)Continental Europe 0.1101## factor(country.study)Israel 0.4471## factor(country.study)South America 0.1790## factor(country.study)UK 0.0758## factor(country.study)USA 0.1986## factor(language)Non-English 0.1481## factor(schizo.core)2 - strong correlate but not core (E-) 0.3132## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.7626## factor(schizo.core)4 - neither core nor correlate 0.2499## factor(schizo.neurot)2 - neurot 0.1064## year 0.0043## age.mean.all2 0.0155#### intrcpt## factor(sample.clinical)2 - clinical## factor(sample.clinical)3 - comparison of clinical and nonclinical## factor(sample.student)2 - nonstudent## factor(sample.student)3 - combined student and nonstudent *## factor(schizo.measure)2 - rating by expert## factor(posneg)2-negative## factor(posneg)3-nonclassified## factor(country.study)Australia and NZ## factor(country.study)Continental Europe## factor(country.study)Israel## factor(country.study)South America## factor(country.study)UK

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## factor(country.study)USA## factor(language)Non-English## factor(schizo.core)2 - strong correlate but not core (E-) .## factor(schizo.core)3 - weak correlate but not core (C-, A-) **## factor(schizo.core)4 - neither core nor correlate## factor(schizo.neurot)2 - neurot## year## age.mean.all2#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.clinical <> Psychoticismres.re.p.sample.clinical <- rma(es, var, mods = ~ factor(sample.clinical)-1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.sample.clinical

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0215 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1467## I^2 (residual heterogeneity / unaccounted variability): 88.80%## H^2 (unaccounted variability / sampling variability): 8.93#### Test for Residual Heterogeneity:## QE(df = 133) = 1923.5924, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 212.5994, p-val < .0001#### Model Results:#### estimate## factor(sample.clinical)1 - nonclinical 0.2002## factor(sample.clinical)2 - clinical 0.3403## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.2616## se## factor(sample.clinical)1 - nonclinical 0.0152## factor(sample.clinical)2 - clinical 0.0907## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0518## zval## factor(sample.clinical)1 - nonclinical 13.1543## factor(sample.clinical)2 - clinical 3.7534## factor(sample.clinical)3 - comparison of clinical and nonclinical 5.0473## pval## factor(sample.clinical)1 - nonclinical <.0001## factor(sample.clinical)2 - clinical 0.0002## factor(sample.clinical)3 - comparison of clinical and nonclinical <.0001## ci.lb## factor(sample.clinical)1 - nonclinical 0.1704## factor(sample.clinical)2 - clinical 0.1626## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.1600## ci.ub## factor(sample.clinical)1 - nonclinical 0.2300## factor(sample.clinical)2 - clinical 0.5181

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## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.3632#### factor(sample.clinical)1 - nonclinical ***## factor(sample.clinical)2 - clinical ***## factor(sample.clinical)3 - comparison of clinical and nonclinical ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.clinical <> Psychoticism: Reference: nonclinicalres.re.p.sample.clinical.r <- rma(es, var, mods = ~ factor(sample.clinical), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.sample.clinical.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0215 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1467## I^2 (residual heterogeneity / unaccounted variability): 88.80%## H^2 (unaccounted variability / sampling variability): 8.93## R^2 (amount of heterogeneity accounted for): 0.94%#### Test for Residual Heterogeneity:## QE(df = 133) = 1923.5924, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 3.4604, p-val = 0.1772#### Model Results:#### estimate## intrcpt 0.2002## factor(sample.clinical)2 - clinical 0.1401## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0614## se## intrcpt 0.0152## factor(sample.clinical)2 - clinical 0.0919## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.0540## zval## intrcpt 13.1543## factor(sample.clinical)2 - clinical 1.5242## factor(sample.clinical)3 - comparison of clinical and nonclinical 1.1363## pval## intrcpt <.0001## factor(sample.clinical)2 - clinical 0.1275## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.2558## ci.lb## intrcpt 0.1704## factor(sample.clinical)2 - clinical -0.0401## factor(sample.clinical)3 - comparison of clinical and nonclinical -0.0445## ci.ub## intrcpt 0.2300## factor(sample.clinical)2 - clinical 0.3204## factor(sample.clinical)3 - comparison of clinical and nonclinical 0.1672##

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## intrcpt ***## factor(sample.clinical)2 - clinical## factor(sample.clinical)3 - comparison of clinical and nonclinical#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.student <> Psychoticismres.re.p.sample.student <- rma(es, var, mods = ~ factor(sample.student) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.sample.student

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0222 (SE = 0.0035)## tau (square root of estimated tau^2 value): 0.1488## I^2 (residual heterogeneity / unaccounted variability): 88.90%## H^2 (unaccounted variability / sampling variability): 9.01#### Test for Residual Heterogeneity:## QE(df = 133) = 1733.2154, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 204.2609, p-val < .0001#### Model Results:#### estimate## factor(sample.student)1 - student 0.2031## factor(sample.student)2 - nonstudent 0.2085## factor(sample.student)3 - combined student and nonstudent 0.2277## se zval## factor(sample.student)1 - student 0.0202 10.0685## factor(sample.student)2 - nonstudent 0.0250 8.3273## factor(sample.student)3 - combined student and nonstudent 0.0393 5.7914## pval ci.lb## factor(sample.student)1 - student <.0001 0.1635## factor(sample.student)2 - nonstudent <.0001 0.1595## factor(sample.student)3 - combined student and nonstudent <.0001 0.1506## ci.ub## factor(sample.student)1 - student 0.2426 ***## factor(sample.student)2 - nonstudent 0.2576 ***## factor(sample.student)3 - combined student and nonstudent 0.3047 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## sample.student <> Psychoticism: Reference: studentres.re.p.sample.student.r <- rma(es, var, mods = ~ factor(sample.student), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.sample.student.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0222 (SE = 0.0035)## tau (square root of estimated tau^2 value): 0.1488

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## I^2 (residual heterogeneity / unaccounted variability): 88.90%## H^2 (unaccounted variability / sampling variability): 9.01## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 133) = 1733.2154, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 0.3104, p-val = 0.8563#### Model Results:#### estimate## intrcpt 0.2031## factor(sample.student)2 - nonstudent 0.0055## factor(sample.student)3 - combined student and nonstudent 0.0246## se zval## intrcpt 0.0202 10.0685## factor(sample.student)2 - nonstudent 0.0322 0.1706## factor(sample.student)3 - combined student and nonstudent 0.0442 0.5570## pval ci.lb## intrcpt <.0001 0.1635## factor(sample.student)2 - nonstudent 0.8645 -0.0575## factor(sample.student)3 - combined student and nonstudent 0.5775 -0.0620## ci.ub## intrcpt 0.2426 ***## factor(sample.student)2 - nonstudent 0.0685## factor(sample.student)3 - combined student and nonstudent 0.1112#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.measure <> Psychoticismres.re.p.schizo.measure <- rma(es, var, mods = ~ factor(schizo.measure) -1,data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.schizo.measure

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0218 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1476## I^2 (residual heterogeneity / unaccounted variability): 88.87%## H^2 (unaccounted variability / sampling variability): 8.98#### Test for Residual Heterogeneity:## QE(df = 134) = 1932.8318, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 207.7346, p-val < .0001#### Model Results:#### estimate se zval## factor(schizo.measure)1 - self-report 0.2046 0.0152 13.4829## factor(schizo.measure)2 - rating by expert 0.2483 0.0487 5.0937

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## pval ci.lb ci.ub## factor(schizo.measure)1 - self-report <.0001 0.1748 0.2343 ***## factor(schizo.measure)2 - rating by expert <.0001 0.1527 0.3438 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.measure <> Psychoticism: Reference: self-reportres.re.p.schizo.measure.r <- rma(es, var, mods = ~ factor(schizo.measure),data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.schizo.measure.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0218 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1476## I^2 (residual heterogeneity / unaccounted variability): 88.87%## H^2 (unaccounted variability / sampling variability): 8.98## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 134) = 1932.8318, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.7336, p-val = 0.3917#### Model Results:#### estimate se zval## intrcpt 0.2046 0.0152 13.4829## factor(schizo.measure)2 - rating by expert 0.0437 0.0510 0.8565## pval ci.lb ci.ub## intrcpt <.0001 0.1748 0.2343 ***## factor(schizo.measure)2 - rating by expert 0.3917 -0.0563 0.1438#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## posneg <> Psychoticismres.re.p.posneg <- rma(es, var, mods = ~ factor(posneg) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.posneg

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0197 (SE = 0.0032)## tau (square root of estimated tau^2 value): 0.1405## I^2 (residual heterogeneity / unaccounted variability): 87.51%## H^2 (unaccounted variability / sampling variability): 8.01#### Test for Residual Heterogeneity:## QE(df = 133) = 1543.9543, p-val < .0001#### Test of Moderators (coefficient(s) 1:3):## QM(df = 3) = 234.8890, p-val < .0001##

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## Model Results:#### estimate se zval pval ci.lb## factor(posneg)1-positive 0.2126 0.0176 12.0611 <.0001 0.1781## factor(posneg)2-negative 0.1481 0.0288 5.1395 <.0001 0.0916## factor(posneg)3-nonclassified 0.2944 0.0371 7.9375 <.0001 0.2217## ci.ub## factor(posneg)1-positive 0.2472 ***## factor(posneg)2-negative 0.2045 ***## factor(posneg)3-nonclassified 0.3671 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## posneg <> Psychoticism: Reference: positiveres.re.p.posneg.r <- rma(es, var, mods = ~ factor(posneg), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.posneg.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0197 (SE = 0.0032)## tau (square root of estimated tau^2 value): 0.1405## I^2 (residual heterogeneity / unaccounted variability): 87.51%## H^2 (unaccounted variability / sampling variability): 8.01## R^2 (amount of heterogeneity accounted for): 9.09%#### Test for Residual Heterogeneity:## QE(df = 133) = 1543.9543, p-val < .0001#### Test of Moderators (coefficient(s) 2:3):## QM(df = 2) = 9.8202, p-val = 0.0074#### Model Results:#### estimate se zval pval ci.lb## intrcpt 0.2126 0.0176 12.0611 <.0001 0.1781## factor(posneg)2-negative -0.0645 0.0338 -1.9110 0.0560 -0.1307## factor(posneg)3-nonclassified 0.0818 0.0411 1.9924 0.0463 0.0013## ci.ub## intrcpt 0.2472 ***## factor(posneg)2-negative 0.0017 .## factor(posneg)3-nonclassified 0.1623 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## es.measure <> Psychoticismres.re.p.es.measure <- rma(es, var, mods = ~ factor(es.measure) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.es.measure

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0218 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1478

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## I^2 (residual heterogeneity / unaccounted variability): 88.90%## H^2 (unaccounted variability / sampling variability): 9.01#### Test for Residual Heterogeneity:## QE(df = 134) = 1934.1038, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 206.9389, p-val < .0001#### Model Results:#### estimate se zval pval## factor(es.measure)1 - correlation 0.2051 0.0153 13.4291 <.0001## factor(es.measure)2 - Cohen's d 0.2392 0.0464 5.1572 <.0001## ci.lb ci.ub## factor(es.measure)1 - correlation 0.1751 0.2350 ***## factor(es.measure)2 - Cohen's d 0.1483 0.3301 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## es.measure <> Psychoticism: Reference: correlationres.re.p.es.measure.r <- rma(es, var, mods = ~ factor(es.measure), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.es.measure.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0218 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1478## I^2 (residual heterogeneity / unaccounted variability): 88.90%## H^2 (unaccounted variability / sampling variability): 9.01## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 134) = 1934.1038, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.4895, p-val = 0.4841#### Model Results:#### estimate se zval pval## intrcpt 0.2051 0.0153 13.4291 <.0001## factor(es.measure)2 - Cohen's d 0.0342 0.0488 0.6997 0.4841## ci.lb ci.ub## intrcpt 0.1751 0.2350 ***## factor(es.measure)2 - Cohen's d -0.0615 0.1299#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## country.study <> Psychoticismres.re.p.country.study <- rma(es, var, mods = ~ factor(country.study) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.country.study

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#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0204 (SE = 0.0033)## tau (square root of estimated tau^2 value): 0.1427## I^2 (residual heterogeneity / unaccounted variability): 87.84%## H^2 (unaccounted variability / sampling variability): 8.22#### Test for Residual Heterogeneity:## QE(df = 129) = 1368.8887, p-val < .0001#### Test of Moderators (coefficient(s) 1:7):## QM(df = 7) = 231.1817, p-val < .0001#### Model Results:#### estimate se zval pval## factor(country.study)Asia 0.3574 0.1052 3.3984 0.0007## factor(country.study)Australia and NZ 0.1666 0.0440 3.7851 0.0002## factor(country.study)Continental Europe 0.1802 0.0307 5.8603 <.0001## factor(country.study)Israel 0.2995 0.1202 2.4921 0.0127## factor(country.study)South America 0.1336 0.0696 1.9189 0.0550## factor(country.study)UK 0.1853 0.0244 7.5999 <.0001## factor(country.study)USA 0.2712 0.0267 10.1643 <.0001## ci.lb ci.ub## factor(country.study)Asia 0.1513 0.5636 ***## factor(country.study)Australia and NZ 0.0803 0.2529 ***## factor(country.study)Continental Europe 0.1199 0.2405 ***## factor(country.study)Israel 0.0640 0.5350 *## factor(country.study)South America -0.0029 0.2701 .## factor(country.study)UK 0.1375 0.2331 ***## factor(country.study)USA 0.2189 0.3235 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## country.study <> Psychoticism: Reference: Asiares.re.p.country.study.r <- rma(es, var, mods = ~ factor(country.study), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.country.study.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0204 (SE = 0.0033)## tau (square root of estimated tau^2 value): 0.1427## I^2 (residual heterogeneity / unaccounted variability): 87.84%## H^2 (unaccounted variability / sampling variability): 8.22## R^2 (amount of heterogeneity accounted for): 6.26%#### Test for Residual Heterogeneity:## QE(df = 129) = 1368.8887, p-val < .0001#### Test of Moderators (coefficient(s) 2:7):## QM(df = 6) = 11.9100, p-val = 0.0640##

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## Model Results:#### estimate se zval pval## intrcpt 0.3574 0.1052 3.3984 0.0007## factor(country.study)Australia and NZ -0.1908 0.1140 -1.6737 0.0942## factor(country.study)Continental Europe -0.1773 0.1096 -1.6175 0.1058## factor(country.study)Israel -0.0579 0.1597 -0.3628 0.7167## factor(country.study)South America -0.2238 0.1261 -1.7742 0.0760## factor(country.study)UK -0.1721 0.1080 -1.5943 0.1109## factor(country.study)USA -0.0863 0.1085 -0.7951 0.4266## ci.lb ci.ub## intrcpt 0.1513 0.5636 ***## factor(country.study)Australia and NZ -0.4143 0.0326 .## factor(country.study)Continental Europe -0.3920 0.0375## factor(country.study)Israel -0.3710 0.2551## factor(country.study)South America -0.4710 0.0234 .## factor(country.study)UK -0.3838 0.0395## factor(country.study)USA -0.2989 0.1264#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## language <> Psychoticismres.re.p.language <- rma(es, var, mods = ~ factor(language) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.language

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0218 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1477## I^2 (residual heterogeneity / unaccounted variability): 88.82%## H^2 (unaccounted variability / sampling variability): 8.95#### Test for Residual Heterogeneity:## QE(df = 134) = 1917.3502, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 207.4326, p-val < .0001#### Model Results:#### estimate se zval pval ci.lb## factor(language)English 0.2164 0.0175 12.3890 <.0001 0.1821## factor(language)Non-English 0.1908 0.0260 7.3448 <.0001 0.1399## ci.ub## factor(language)English 0.2506 ***## factor(language)Non-English 0.2417 ***#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## language <> Psychoticism: Reference: Englishres.re.p.language.r <- rma(es, var, mods = ~ factor(language), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.language.r

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#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0218 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1477## I^2 (residual heterogeneity / unaccounted variability): 88.82%## H^2 (unaccounted variability / sampling variability): 8.95## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 134) = 1917.3502, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.6679, p-val = 0.4138#### Model Results:#### estimate se zval pval ci.lb## intrcpt 0.2164 0.0175 12.3890 <.0001 0.1821## factor(language)Non-English -0.0256 0.0313 -0.8173 0.4138 -0.0869## ci.ub## intrcpt 0.2506 ***## factor(language)Non-English 0.0358#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## year <> Psychoticismres.re.p.year <- rma(es, var, mods = ~ year, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.year

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0217 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1474## I^2 (residual heterogeneity / unaccounted variability): 88.73%## H^2 (unaccounted variability / sampling variability): 8.87## R^2 (amount of heterogeneity accounted for): 0.00%#### Test for Residual Heterogeneity:## QE(df = 134) = 1602.5697, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 0.2697, p-val = 0.6036#### Model Results:#### estimate se zval pval ci.lb ci.ub## intrcpt 1.6481 2.7725 0.5945 0.5522 -3.7859 7.0822## year -0.0007 0.0014 -0.5193 0.6036 -0.0034 0.0020#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

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## age.mean.all2 <> Psychoticismres.re.p.age.mean.all2 <- rma(es, var, mods = ~ age.mean.all2, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))

## Warning in rma(es, var, mods = ~age.mean.all2, data = dat.analysis, subset## = (dat.analysis$trait == : Studies with NAs omitted from model fitting.res.re.p.age.mean.all2

#### Mixed-Effects Model (k = 105; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0173 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1316## I^2 (residual heterogeneity / unaccounted variability): 78.17%## H^2 (unaccounted variability / sampling variability): 4.58## R^2 (amount of heterogeneity accounted for): 3.15%#### Test for Residual Heterogeneity:## QE(df = 103) = 437.7260, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 3.8890, p-val = 0.0486#### Model Results:#### estimate se zval pval ci.lb ci.ub## intrcpt 0.0769 0.0691 1.1136 0.2655 -0.0585 0.2123## age.mean.all2 0.0053 0.0027 1.9721 0.0486 0.0000 0.0105 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.core <> Psychoticismres.re.p.schizo.core <- rma(es, var, mods = ~ factor(schizo.core) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.schizo.core

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0156 (SE = 0.0026)## tau (square root of estimated tau^2 value): 0.1249## I^2 (residual heterogeneity / unaccounted variability): 84.32%## H^2 (unaccounted variability / sampling variability): 6.38#### Test for Residual Heterogeneity:## QE(df = 132) = 941.7551, p-val < .0001#### Test of Moderators (coefficient(s) 1:4):## QM(df = 4) = 308.5590, p-val < .0001#### Model Results:#### estimate## factor(schizo.core)1 - core schizotypy content 0.2026## factor(schizo.core)2 - strong correlate but not core (E-) 0.1867

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## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.4332## factor(schizo.core)4 - neither core nor correlate 0.0835## se## factor(schizo.core)1 - core schizotypy content 0.0148## factor(schizo.core)2 - strong correlate but not core (E-) 0.0409## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0440## factor(schizo.core)4 - neither core nor correlate 0.0446## zval## factor(schizo.core)1 - core schizotypy content 13.6846## factor(schizo.core)2 - strong correlate but not core (E-) 4.5591## factor(schizo.core)3 - weak correlate but not core (C-, A-) 9.8492## factor(schizo.core)4 - neither core nor correlate 1.8700## pval## factor(schizo.core)1 - core schizotypy content <.0001## factor(schizo.core)2 - strong correlate but not core (E-) <.0001## factor(schizo.core)3 - weak correlate but not core (C-, A-) <.0001## factor(schizo.core)4 - neither core nor correlate 0.0615## ci.lb## factor(schizo.core)1 - core schizotypy content 0.1736## factor(schizo.core)2 - strong correlate but not core (E-) 0.1064## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.3470## factor(schizo.core)4 - neither core nor correlate -0.0040## ci.ub## factor(schizo.core)1 - core schizotypy content 0.2316 ***## factor(schizo.core)2 - strong correlate but not core (E-) 0.2669 ***## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.5194 ***## factor(schizo.core)4 - neither core nor correlate 0.1710 .#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.core <> Psychoticism: Reference: core schizotypy contentres.re.p.schizo.core.r <- rma(es, var, mods = ~ factor(schizo.core), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.schizo.core.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0156 (SE = 0.0026)## tau (square root of estimated tau^2 value): 0.1249## I^2 (residual heterogeneity / unaccounted variability): 84.32%## H^2 (unaccounted variability / sampling variability): 6.38## R^2 (amount of heterogeneity accounted for): 28.19%#### Test for Residual Heterogeneity:## QE(df = 132) = 941.7551, p-val < .0001#### Test of Moderators (coefficient(s) 2:4):## QM(df = 3) = 34.3632, p-val < .0001#### Model Results:#### estimate## intrcpt 0.2026## factor(schizo.core)2 - strong correlate but not core (E-) -0.0159

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## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.2307## factor(schizo.core)4 - neither core nor correlate -0.1191## se## intrcpt 0.0148## factor(schizo.core)2 - strong correlate but not core (E-) 0.0435## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.0464## factor(schizo.core)4 - neither core nor correlate 0.0470## zval## intrcpt 13.6846## factor(schizo.core)2 - strong correlate but not core (E-) -0.3652## factor(schizo.core)3 - weak correlate but not core (C-, A-) 4.9701## factor(schizo.core)4 - neither core nor correlate -2.5322## pval## intrcpt <.0001## factor(schizo.core)2 - strong correlate but not core (E-) 0.7149## factor(schizo.core)3 - weak correlate but not core (C-, A-) <.0001## factor(schizo.core)4 - neither core nor correlate 0.0113## ci.lb## intrcpt 0.1736## factor(schizo.core)2 - strong correlate but not core (E-) -0.1012## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.1397## factor(schizo.core)4 - neither core nor correlate -0.2113## ci.ub## intrcpt 0.2316 ***## factor(schizo.core)2 - strong correlate but not core (E-) 0.0694## factor(schizo.core)3 - weak correlate but not core (C-, A-) 0.3216 ***## factor(schizo.core)4 - neither core nor correlate -0.0269 *#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.neurot <> Psychoticismres.re.p.schizo.neurot <- rma(es, var, mods = ~ factor(schizo.neurot) -1, data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.schizo.neurot

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0215 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1467## I^2 (residual heterogeneity / unaccounted variability): 88.72%## H^2 (unaccounted variability / sampling variability): 8.86#### Test for Residual Heterogeneity:## QE(df = 134) = 1902.7903, p-val < .0001#### Test of Moderators (coefficient(s) 1:2):## QM(df = 2) = 210.9210, p-val < .0001#### Model Results:#### estimate se zval pval## factor(schizo.neurot)1 - schizo 0.2119 0.0146 14.4660 <.0001## factor(schizo.neurot)2 - neurot 0.1044 0.0811 1.2870 0.1981## ci.lb ci.ub

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## factor(schizo.neurot)1 - schizo 0.1832 0.2406 ***## factor(schizo.neurot)2 - neurot -0.0546 0.2633#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## schizo.neurot <> Psychoticism: Reference: schizores.re.p.schizo.neurot.r <- rma(es, var, mods = ~ factor(schizo.neurot), data=dat.analysis, subset = (dat.analysis$trait == "3 - Psychoticism"))res.re.p.schizo.neurot.r

#### Mixed-Effects Model (k = 136; tau^2 estimator: REML)#### tau^2 (estimated amount of residual heterogeneity): 0.0215 (SE = 0.0034)## tau (square root of estimated tau^2 value): 0.1467## I^2 (residual heterogeneity / unaccounted variability): 88.72%## H^2 (unaccounted variability / sampling variability): 8.86## R^2 (amount of heterogeneity accounted for): 0.98%#### Test for Residual Heterogeneity:## QE(df = 134) = 1902.7903, p-val < .0001#### Test of Moderators (coefficient(s) 2):## QM(df = 1) = 1.7027, p-val = 0.1919#### Model Results:#### estimate se zval pval## intrcpt 0.2119 0.0146 14.4660 <.0001## factor(schizo.neurot)2 - neurot -0.1075 0.0824 -1.3049 0.1919## ci.lb ci.ub## intrcpt 0.1832 0.2406 ***## factor(schizo.neurot)2 - neurot -0.2690 0.0540#### ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Compute n´s per mean correlation coefficient ####

increment <- function (curr_n, i){n = dat.analysis$n.schizo[i];

if(!is.na(dat.analysis$r[i])){return (curr_n + n);

}else {

return (curr_n + n + dat.analysis$n.control[i]);}

}

dat.analysis <- import("datAnalysis.csv")

length <- length(dat.analysis$n.schizo)

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n_e = n_n = n_p = 0

for (i in 1:length){trait = dat.analysis$trait[i];if (trait == "1 - Neuroticism"){

n_n = increment(n_n, i);}else if (trait == "2 - Extraversion"){

n_e = increment(n_e, i)}else if (trait == "3 - Psychoticism"){

n_p = increment(n_p, i)}

}

print (n_e)

## [1] 35648print (n_p)

## [1] 42880print (n_n)

## [1] 37080

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