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Toggweiler (2018) 1 Regression function and explained variance of NEO-PI-R Big Five graphology as valid observer-assessment. Stephan Toggweiler INTRODUCTION GraphoPro as a tool for data collection of handwriting signs GraphoPro (Keel, 2016) by dipl. Psych., ingeneer FH and graphologist Bruno Keel is a software, which enables the systematic recording of handwriting signs. GraphoPro is an open system, the integrated handwriting signs have been collected in the relevant literature and can be easily supplemented. At the moment 234 handwriting signs are programmed in GraphoPro, e. g. conspicuous, determined, weakly printed, etc. They are coded in four levels (characteristic does not exist, characteristic occurs, characteristic is clearly present, characteristic dominates). Figure 1. GraphoPro user interface. NEO-PI-R from Ostendorf and Angleitner (2004) In order to be able to assess the impact of the handwriting signs of GraphoPro in the sense of a construct validation, and in order to optimise GraphoPro in this respect, the five Big Five scales (Table 1) of the NEO-PI-R (Ostendorf & Angleitner, 2004) were included. The aim is to predict these

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Page 1: Regression function and explained variance of NEO-PI-R Big ... · The NEO-PI-R was chosen because it is a well differentiated and widely used test. The NEO-PI-R is based on the German

Toggweiler (2018) 1

Regression function and explained variance of NEO-PI-R Big Five –

graphology as valid observer-assessment.

Stephan Toggweiler

INTRODUCTION

GraphoPro as a tool for data collection of handwriting signs

GraphoPro (Keel, 2016) by dipl. Psych., ingeneer FH and graphologist Bruno Keel is a software,

which enables the systematic recording of handwriting signs. GraphoPro is an open system, the

integrated handwriting signs have been collected in the relevant literature and can be easily

supplemented. At the moment 234 handwriting signs are programmed in GraphoPro, e. g. conspicuous,

determined, weakly printed, etc. They are coded in four levels (characteristic does not exist,

characteristic occurs, characteristic is clearly present, characteristic dominates).

Figure 1. GraphoPro user interface.

NEO-PI-R from Ostendorf and Angleitner (2004)

In order to be able to assess the impact of the handwriting signs of GraphoPro in the sense of a

construct validation, and in order to optimise GraphoPro in this respect, the five Big Five scales (Table

1) of the NEO-PI-R (Ostendorf & Angleitner, 2004) were included. The aim is to predict these

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Toggweiler (2018) 2

characteristics by means of the handwriting signs. If this should succeed, a personality test could be

replaced through graphological analysis. The NEO-PI-R was chosen because it is a well differentiated

and widely used test. The NEO-PI-R is based on the German translation of the Revised NEO

Personality Inventory of Costa and McCrae (1992; McCrae & Costa, 1996,1999). It serves to evaluate

basic personality traits, the so-called Big Five: Neuroticism, extraversion, openness to experience,

agreeableness, and conscientiousness. Each of these dimensions is divided into six subscales with

eight items each. This allows a very differentiated measurement of the five superior personality traits

as well as 30 sub-facets of personality. The advantage of the NEO-PI-R is its wide range of personal

characteritics, which is captured and identifies the test as a screening instrument. To name just a few

arreas of its application the NEO-PI-R is used in counselling, clinical psychology and psychiatry, in

behavioural medicine and health psychology, in career counselling, in occupational, industrial and

organisational psychology and in research (Ostendorf & Angleitner, 2004, p. 4). The NEO-PI-R is a

validated standard instrument (Ostendorf & Angleitner, 2004, p. 140ff), easy to use, well known and it

has been translated into more than 30 languages. There is as well a version available that enables an

observer-assessments, e. g. by family members or close acquaintances. The following Table 1 shows

the scales and sub-scales of the NEO-PI-R including examples of items.

Table 1. The Big Five dimensions of the NEO-PI-R (Ostendorf & Angleitner, 2004)

Scales Subscales (examples)

Neuroticism (p. 33f.) Persons with a high level of neuroticism are more sensitive and tend to

lose their balance more easily under stress. In stressful situations, they tend

to be more often annoyed, sad, embarrassed, anxious, ashamed, distressed

and worried. They also tend to develop more inappropriate forms of

problem solving, tend to have unrealistic ideas and are less able to control

their needs. Persons with high level of these characteristics can be

characterised with the following adjectives: Tensioned, needy, anxious,

worried, alarmed, emotional, sensitive, irritable, helpless, helpless, moody,

nervous, self-pitying, self-doubting, hypersensitive, unbalanced, restless,

insecure, unhappy, unsatisfied, vulnerable and snivelling.

Anxiety (I'm not easily to be worried)

Angry-Hostility (I often get angry about

how other people treat me)

Depression (I rarely feel lonely or sad)

Self-consciousness (I'm often afraid that I

might attract unpleasant attention when

dealing with others)

Impulsivity (I seldom get too involved in

anything)

Vulnerability (I often feel helpless and

wish a person to solve my problems)

Extraversion (p. 40f.) In everyday language, people with a high degree of extraversion can be

described as sociable, talkative, friendly, enterprising and active.

Extraverted people like the company of others, they feel comfortable in

groups, but are also assertive, self-confident, dominant, love exciting

situations and stimuli. They tend to be optimistic, cheerful and entertaining

[...]. According to Costa and McCrae (1992, p. 15), introversion should be

understood as a lack rather than an opposition to extraversion. Descriptive

adjectives for an extroverted person: Adventurous, active, bright,

enthusiastic, dominant, dynamic, fiery, cheerful, friendly, chatty, sociable,

talkative, cordial, likes to be funny, lively, passionate, courageous,

optimistic, person-oriented, talkative, communicative, assertive,

spontaneous and temperate.

Warmth (Most people I meet are really

likeable for me)

Gregariousness (I like to have a lot of

people around me)

Assertiveness (I am dominant, self-

confident and assertive)

Activity (I work and play in a leisurely

way)

Excitement-Seeking (I often long to

experience more exciting things)

Positive emotions (I've never really jumped

up in the air with joy)

Openness to Experience (p. 42f.)

People with high level of openness to experience are interested in new

experiences and impressions. They are interested in the outside world, but

also in their inner world. They claim to have a lively fantasy and to

perceive their own positive and negative feelings very clearly. They

embrace new ideas and are unconventional in their value orientations.

They describe themselves as being interested in a variety of subjects,

interested in knowledge, creative and interested in theories and cultural

events, inclined to critically question existing norms and values and

willing to deal with new ethical, political and social issues and

orientations. […] A high level of openness to experience can be described

with the following adjectives: Imaginative, sentient, inventive, sensitive,

progressive, witty, has many interests, full of ideas, creative, critical,

liberal, musical, curious, non-conformist, open, original, unconventional,

and eager to learn.

Openness to Fantasy (I have a very lively

imagination)

Openness to Aesthetics (Aesthetics and art

mean a lot to me)

Openness to Feelings (Without strong

feelings life would be uninteresting for me)

Openness to Actions (I am quite used to my

courses)

Openness to Ideas (I often have fun playing

with theories or abstract ideas)

Openness to Values (I believe that it is

often confusing and misleading for students

to listen to speakers who take controversial

points of view)

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Toggweiler (2018) 3

Agreeableness (p. 44f.)

A person with a high level of agreeableness can be characterised as

helpful, accommodating, trusting and eager to help others. In addition,

such a person is usually convinced that other people as well react with

helpfulness. Persons with a high degree of tolerance are open to other

people with benevolence, tend to be good-natured, are willing to give in in

disputes and may in extreme cases appear to be submissive or dependent.

A pathological extreme variant is the personality disorder of the

"dependent personality". Characteristic adjectives for high level of

agreeableness are as follows: Altruistic, undemanding, innocent, self-

sacrificing, sincere, unambitious, modest, direct, honest, accommodating,

free, outspoken, kind, pleasing, straightforward, generous, trustful, good-

natured, willing, helpful, gullible, credulous, and sympathetic.

Trust (I am rather cynical and sceptical

about the intentions of others)

Straightforwardness (I don't think I'm

cunning)

Altruism (Some people think I'm selfish

and complacent)

Compliance (I would rather work with

others than compete with them)

Modesty (I don't mind stating my skills and

achievements)

Tender-Mindedness (Politicians should

care more about the human side of their

policies)

Conscientiousness (p. 45f.)

People with a high degree of conscientiousness describe themselves as

determined, strong-willed and purposeful. Only a few people become great

musicians or sportsmen without a fairly high expression in

conscientiousness. Digman and Takemoto-Chock (1981) describe this

range of characteristics as "will to achieve". High level corresponds to

academic and professional achievement. On the other hand, an

exaggeratedly high level of demands, almost compulsive neatness and

workaholism can be seen as negative examples of high level of

conscientiousnes. A high level of of conscientiousness can be outlined by

the following adjectives: Hardworking, persistent, prudent, ambitious,

eager, diligent, precise, conscientious, competent, efficient, motivated,

orderly, tidy, disciplined, dutiful, committed, planned, principled,

punctual, righteous, self-disciplined, careful and systemic.

Competence (I am known for my prudence

and my senses)

Order (I prefer to leave myself free from

decisions instead of planning everything in

advance)

Dutifullness (I try to do all the tasks

assigned to me very conscientiously)

Achievement Striving (I am carefree and

indifferent)

Self-Discipline (I can allocate my time

quite well, so that I can finish my business

in time)

Deliberation (I've done some stupid things

in my life)

These scales and subscales are measured on the basis of 240 items scaled at five grades (strong

rejection – rejection – neutral – approval – strong agreement). The completion of the questionnaire

takes about 30 - 40 minutes, but there is no time limit. The target group of the NEO-PI-R is people

over 16 years of age.

Research Questions

This publication answers two questions:

1. Is it possible to construct reliable graphological scales of the Big Five dimensions via

GraphoPro and NEO-PI-R?

2. What is the quality of this solution in terms of convergent validity between the graphological

scales and the Big Five dimensions?

Relevance of the study

The relevance of this study is based on the fact that the author is not aware of any studies which have

attempted to construct valid graphological scales by means of a more or less standardised

psychometrical approach and to predict or rather to diagnose the characteristics of the NEO-PI-R self-

assessment. If in this way it should be possible to construct graphological scales based on an

established psychometrical instrument, a significant step towards validity methodology of

graphological characteristics is likely to be taken.

METHOD

Instruments

For answering the research questions, the GraphoPro software described above and the NEO-PI-R

(Ostendorf & Angleitner, 2004) were used.

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Toggweiler (2018) 4

Recruting of the sample

The sample was obtained based on a chance approach. The potential participants were contacted by

Bruno Keel and Etienne Bühler (student ZHAW) and were asked to take part in the survey. Both of

them did not know each other's candidates. Approximately 300 people were asked to participate in the

study, whereas 121 have agreed to submit a handwriting sample and fill out the NEO-PI-R

questionnaire.

Obtaining the NEO-PI-R data

The participants received an instruction on the handwriting sample (by e-mail), together with the

NEO-PI-R questionnaire (by mail). Participants were instructed to write one page about any topic of

their choice on an unlined A4 page with a ballpoint pen. In addition, they were instructed to use five

A4 sheets as a pad and to provide their signature as well. Participants were asked not to use any

writing aids or lined patterns. All handwriting samples were then evaluated using GraphoPro's 234

handwriting signs. The handwriting signs were coded by Bühler or Keel and were cross-checked.

Data cleaning

Missing values in the NEO-PI-R were not replaced. 18 Participants had to be excluded because they

did not fully follow the instructions for the handwriting sample. This resulted in a sample of 103

persons.

Additional sample from the GraphoPro database

At the time of data collection, there were already 98 completely coded handwriting samples in

GraphoPro, but without NEO-PI-R inquiery. Psychologists and graphologists Christian Katz, Bruno

Keel, Roman Krapf and Martin Leisebach coded these handwriting samples. In each case, it was

ensured that at least one graphologist was involved as second coder who did not know the author of

the the handwriting sample.

Statistical procedures

For the statistical analysis the following procedures were used: Descriptive statistics, cluster analyses

(method complete linkage, distance measure as Pearson correlation), correlation analyses, item and

scale analyses, and multiple linear regressions (method enter). The raw values of the graphological

scales were calculated by averaging.

RESULTS

Description of the sample

As shown in Table 1, the gender of the participants was approximately equally distributed within the

whole sample with 51.7 % women and 48.3 % men, and 59.2 % women and 40.8 % men for the NEO-

PI-R sample. 32.3 % of the participants have an academic education, 27.4 % have a high-school or a

special professional education, and 15.9 % were registered for a secondary school or high school at the

time of the research. These relations are also preserved more or less in the NEO-PI-R sample, whereby

the candidates are in average about seven years younger.

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Toggweiler (2018) 5

Table 2. Description of samples

Whole Sample

(1)

NEO-PI-R

Sample (2)

Characteristic n (%) n (%)

Gender

Feminine 104 (51.7) 61 (59.2)

Masculine 97 (48.3) 42 (40.8)

Age (M1 = 50.45, SD1 = 20.91 resp. M2 = 42.00, SD2 = 15.06)

18 – 25 years

16 (8.0)

10 (9.7)

26 – 35 years 45 (22.4) 34 (33.0)

36 – 55 years 66 (32.8) 35 (34.0)

> 55 years 74 (36.8) 24 (23.3)

Educational level

Unfinished lower secondary school - -

Lower secondary school 4 (2.0) 4 (3.9)

Apprenticeship without national vocational qualification - -

National vocational qualification, not yet certificated 6 (3.0) 6 (5.8)

National vocational qualification 36 (17.9) 24 (23.3)

Upper secondary school, not yet certificated 26 (12.9) 11 (10.7)

Upper secondary school 5 (2.5) 5 (4.9)

Upper secondary school and ongoing higher education qualification 14 (7.0) 14 (13.6)

Upper secondary school and higher education qualification 65 (32.3) 39 (37.9)

Missing information 45 (22.4) -

Handedness

Left 11 (5.5) 10 (9.7)

Right 190 (94.5) 93 (90.3)

Question 1: Scale construction

First approach – Scale construction via cluster analysis

Via cluster analysis (method complete linkage, distance measure Pearson correlation) a total of 13

clusters were found at a distance of 15. These clusters had the following reliability in terms of

Cronbach's Alpha: .89 (13 handwriting signs), . 88 (24 handwriting signs), .62 (11 handwriting

signs), .90 (20 handwriting signs), .73 (22 handwriting signs), .56 (6 handwriting signs), .87 (15

handwriting signs), .81 (15 handwriting signs), .90 (22 handwriting signs), .93 (25 handwriting

signs), .81 (26 handwriting signs), .86 (19 handwriting signs) and .81 (15 handwriting signs). Both

Pearson correlations and multiple linear regressions, however, showed no significant connections

(explanation of variance) with the Big Five dimensions of at least a medium effect.

Second approach – Scale construction via correlation analysis

With the next approach, it was examined whether the desired association of personality to the

graphological scales could be achieved by means of correlation analysis. In order to construct these

scales, all handwriting signs with significant and highest positive (indexed with +) and significant and

highest negative (indexed with -) correlations were combined with the corresponding dimensions of

the NEO-PI-R. Table 3 shows these Pearson correlations (the original German names of the

handwriting signs are preserved). It can be seen that they rarely are above .30, which would be

equivalent to a medium effect size. Regarding the distributions of the handwriting signs it can be

mentioned that skewness and/or kurtosis exceed the critical value of 2.00 for 17 out of 68 handwriting

signs. However the optical check shows that these handwriting signs are at least unimodal. On the

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Toggweiler (2018) 6

other hand, the discriminative powers are clearly inadequate in 26 cases with values less than .30. The

Cronbach's Alpha of the graphological scales is .24 (agreeableness+), .38 (openness to experience

+)

and .86 (extraversion-). Two graphological scales (agreeableness

- and conscientiousness

+) could only

be formed by just one handwriting sign, so there is no Cronbach’s Alpha available. One handwriting

sign (“fein”) within the scale openness to experience- had to be recoded due to its negative

discriminative power.

Table 3. Descriptives, Pearson correlations and psychometrics of handwriting signs and graphological scales

Descriptives (N = 201) Pearson correlations (N = 103) Scale characteristics

(N = 201)

M SD Skew Curt N E O A C rit α-i α-

Neuroticism+ 0.63 0.40 0.73 -0.11 .71

Längenunterschied klein 0.55 0.81 1.16 0.11 .20* .00 -.04 -.14 .05 .43 .68

unauffällig 0.43 0.73 1.51 1.14 .20* -.11 .11 -.06 .02 .06 .72

linksläufig 0.55 0.62 0.68 -0.50 .21* .03 .00 .11 .02 .34 .69

voll 0.82 0.95 0.72 -0.79 .20* .08 -.06 -.09 -.02 .49 .67

binneneng 0.78 0.95 0.88 -0.43 .28** -.01 -.17 -.03 -.05 .54 .66

Wortabstand klein 0.31 0.60 1.81 2.06 .24* .06 .02 -.09 -.10 .29 .70

langsam 0.45 0.76 1.57 1.53 .20* .02 -.03 -.05 -.11 .37 .69

zögernd 0.22 0.49 2.42 6.59 .23* .04 .04 -.15 -.14 .31 .70

Oberzeichen tief 0.78 0.86 0.92 0.16 .23* -.04 -.13 -.20* -.16 .38 .68

endbetont 0.46 0.67 1.24 0.69 .22* -.01 -.01 .01 -.16 .06 .72

schmale Ränder 1.01 1.05 0.53 -1.06 .31*** .17 .15 -.02 -.17 .37 .69

Linksrand schmal 1.14 1.16 0.41 -1.36 .31** .13 .06 -.18 -.26** .44 .68

Neuroticism- 0.85 0.77 0.68 -0.26 .59

Zeile gerade 1.15 1.00 0.21 -1.20 -.24* .04 -.12 .05 .21* .42

Zeile straff 0.56 0.83 1.30 0.66 -.21* -.10 -.09 .15 .20* .42

Extraversion+ 0.70 0.41 0.73 0.13 .66

unübersichtlich 0.38 0.73 1.80 2.15 -.01 .24* .16 -.03 .16 .27 .65

Unterlängen offen 0.82 0.99 0.88 -0.44 -.03 .22* .11 -.03 .07 .29 .65

schlaff 0.19 0.45 2.38 5.13 -.06 .23* .12 -.12 .04 .12 .67

primitiv 0.58 0.82 1.07 -0.11 .11 .35*** .07 -.18 .01 .61 .59

teigig 0.47 0.73 1.52 1.69 .06 .28** .18 -.11 -.01 .15 .67

üppig 0.68 0.86 1.09 0.29 .09 .21* -.07 -.13 -.02 .35 .64

ungeordnet 0.30 0.66 2.14 3.71 .08 .19* .14 .07 -.04 .26 .65

Unterschrift ungleich 1.00 1.15 0.67 -1.09 .08 .28** .04 -.08 -.04 .42 .62

gross 1.04 0.98 0.42 -1.00 .11 .21* .13 -.07 -.05 .29 .65

leserlich 1.71 1.01 -0.36 -0.95 .12 .20* .00 -.01 -.06 .21 .67

undifferenziert 0.54 0.82 1.15 -0.17 .12 .29** .01 -.10 -.07 .50 .61

Extraversion- 0.58 0.42 1.04 0.49 .86

sachlich 0.78 0.83 0.71 -0.45 -.16 -.20* -.02 -.02 .16 .31 .86

Endfaden 0.23 0.57 2.67 7.03 -.08 -.25* .03 .14 .14 .27 .86

gespannt 0.67 0.80 0.91 -0.12 .03 -.25* -.09 .05 .13 .19 .86

Faden 0.34 0.67 1.84 2.17 -.06 -.31*** .09 .08 .11 .48 .85

nüchtern 0.67 0.90 1.05 -0.11 -.10 -.24* .09 -.06 .10 .65 .85

geöffnet 0.63 0.80 0.95 -0.19 -.11 -.20* .03 .05 .07 .58 .85

reserviert 0.35 0.65 1.76 2.17 -.06 -.21* -.01 -.07 .06 .01 .87

leicht 0.53 0.76 1.16 0.19 -.17 -.26** -.05 -.07 .02 .49 .85

schwer leserlich 0.56 0.80 1.21 0.36 -.09 -.22* -.08 -.02 .01 .44 .86

vereinfacht 1.05 0.95 0.49 -0.74 -.15 -.25* -.03 -.03 .01 .68 .84

Doppelbogen 0.36 0.65 1.82 2.80 -.02 -.28** .18 .03 .01 .35 .86

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Toggweiler (2018) 7

Descriptives (N = 201) Pearson correlations (N = 103) Scale characteristics

(N = 201)

M SD Skew Curt N E O A C rit α-i α-

kühl 0.54 0.77 1.13 0.06 -.03 -.22* .00 -.05 -.01 .46 .85

Unterlängen mager 0.62 0.88 1.15 0.12 -.03 -.26** -.16 -.20* -.02 .35 .86

rechtsläufig 0.76 0.87 0.72 -0.73 -.09 -.26** -.02 -.08 -.02 .54 .85

offen 0.58 0.88 1.33 0.64 -.02 -.23* .06 .04 -.03 .45 .86

binnenweit 0.51 0.79 1.43 1.07 -.03 -.23* -.06 .05 -.05 .51 .85

karg 0.56 0.90 1.36 0.53 -.03 -.31*** -.01 -.08 -.05 .75 .84

geistig 0.63 0.80 1.12 0.60 -.10 -.26** -.04 -.04 -.06 .54 .85

endunterbetont 0.59 0.76 0.98 -0.12 .06 -.22* -.07 .00 -.09 .27 .86

formschwach 0.59 0.90 1.36 0.77 -.05 -.23* .04 -.14 -.15 .56 .85

Openness to Experience+ 0.49 0.42 0.96 0.82 .38

Unterlängen voll 0.69 0.85 0.90 -0.36 .01 .07 .21* -.06 .05 .10 .41

Druck gestaut 0.29 0.59 2.03 3.60 .12 .17 .23* .12 -.04 .14 .37

schmaler oberer Rand 0.64 1.00 1.30 0.30 .21* .12 .24* .18 -.17 .16 .37

ungleichmässig 0.54 0.76 1.42 1.58 .04 .14 .20* -.03 -.20* .26 .28

unsicher 0.28 0.60 2.26 5.03 .14 .21* .28** -.05 -.25* .37 .22

Openness to Experience- 1.38 0.45 -0.12 -0.39 .57

fein (recodiert) 2.56 0.77 -1.67 1.94 .03 -.07 -.22* -.06 -.15 .04 .60

sicher eingeteilt 1.42 0.97 -0.23 -1.05 -.20* -.15 -.25* -.04 .17 .35 .51

prägnant 1.06 0.92 0.26 -1.05 -.13 -.16 -.27** .06 .14 .44 .48

geordnet 1.50 0.99 -0.15 -1.02 -.10 -.22* -.25* .04 .12 .23 .55

bestimmt 1.79 0.90 -0.45 -0.47 .03 -.01 -.21* -.05 .07 .49 .46

gestaltet 0.98 0.92 0.66 -0.41 .08 .07 -.20* .08 .04 .27 .54

drängend 0.83 0.83 0.44 -1.11 -.06 -.02 -.23* .05 .00 .10 .59

hart 0.92 0.82 0.43 -0.72 .09 -.16 -.30** .06 -.07 .29 .53

Agreeableness+ 0.41 0.42 1.26 2.28 .24

Unterlängen eckig 0.32 0.69 2.23 4.29 -.13 .05 -.02 .21* .14 .15 .12

gelötet 0.24 0.50 2.17 5.51 -.13 -.07 .08 .24* .12 .14 .17

reich 0.67 0.79 0.91 -0.02 .02 -.03 .05 .21* .05 .11 .23

Agreeableness- 0.65 0.93 1.26 0.45 -

breiter oberer Rand 0.65 0.93 1.26 0.45 -.07 -.05 -.18 -.26** .06 - -

Conscientiousness+ 1.40 1.02 -0.11 -1.18 -

gleichmässig 1.40 1.02 -0.10 -1.18 -.05 -.02 -.05 .06 .20* - -

Conscientiousness- 0.46 0.47 1.83 4.22 .71

Zeile schwankend 0.74 0.70 0.51 -0.53 .17 .03 .12 -.16 -.20* .34 .72

unrhythmisch 0.46 0.79 1.52 1.11 .14 .12 -.01 .10 -.23* .55 .64

ungeschickt 0.24 0.58 2.78 8.21 .11 .18 .22* -.02 -.25* .61 .62

gebremst 0.55 0.70 0.89 -0.46 .21* .05 -.07 .11 -.25** .39 .70

haltlos 0.29 0.65 2.21 3.96 .00 .02 .00 -.07 -.32*** .51 .65

Note. * p ** p *** p Potential range of items is 0 to 3. M = Mean, SD = Standard deviation, Skew = Skewness, Curt =

Curtosis, rit = Discriminative power, α = Cronbach’s Alpha, α-i = Cronbach’s Alpha without item. Bold are convergent correlations of

handwriting signs and NEO-PI-R.

Question 2: Explained Variance

The following Table 4 shows the Pearson correlations of the graphological scales with the Big Five

dimensions of the NEO-PI-R. The significant convergent correlations range from .20 to .49, which

corresponds to an explained variance of 4.00 respectively 24.01 %. Five out of ten correlations achieve

medium convergent validity, i.e. the correlations reach values between .40 and .59.

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Toggweiler (2018) 8

Table 4. Pearson correlations and explained variance between graphological scales and NEO-PI-R.

N E O A C

Neuroticism+ .44*** (r2 = .19) .07 -.01 -.15 -.18

Neuroticism- -.27** (r2 = .07) -.03 -.13 .12 .25*

Extraversion+ .13 .45*** (r2 = .20) .14 -.13 -.01

Extraversion- -.11 -.40*** (r2 =.16) -.01 -.05 .02

Openness to

Experience+ .19 .24* .42*** (r2 = .18) .06 -.23*

Openness to

Experience- -.08 -.19 -.49*** (r2 = .24) .04 .10

Agreeableness+ -.09 -.04 .06 .35*** (r2 = .12) .15

Agreeableness- -.07 -.05 -.18 -.26** (r2 = .07) .06

Conscientiousness+ -.05 -.02 -.05 .06 .20* (r2 = .04)

Conscientiousness- .17 .11 .06 .00 -.35*** (r2 = .12)

Note. N = 103. * p ** p *** p ld are medium validity coefficients (.40 r < .60).

Results of linear multiple regressions indicated that all five prediction models of the NEO-PI-R

dimensions were statistically significant, whereas for neuroticism F(10, 92) = 4.07, p <.001, for

extraversion F(10, 92) = 6.14, p < .001, for openness to experience F(10, 92) = 7.02, p < .001, for

agreeableness F(10, 92) = 3.28, p = .001 and for conscientiousness F(10, 92) = 2.33, p < .05.

Page 9: Regression function and explained variance of NEO-PI-R Big ... · The NEO-PI-R was chosen because it is a well differentiated and widely used test. The NEO-PI-R is based on the German

Toggweiler (2018) 9

N

euro

tici

sm

Extr

aver

sion

O

pen

nes

s to

exp

erie

nce

A

gre

eab

len

ess

Con

scie

nti

ou

snes

s

B

S

E(B

) 𝛽

t

B

SE

(B)

𝛽

t B

S

E(B

) 𝛽

t

B

SE

(B)

𝛽

t B

S

E(B

) 𝛽

t

Con

stan

t 6

5.6

1

14.4

6

4

.54

***

129

.96

11.6

5

1

1.1

5***

145

.33

9.1

9

1

5.8

2***

136

.59

11.2

0

1

2.1

9***

123

.75

14.3

9

8

.60

***

Neu

roti

cism

+

31.4

5

6.2

3

.64

5.0

5***

-21

.93

5.0

2

-.5

2

-4.3

7***

-8.7

3

3.9

6

-.2

5

-2.2

0*

-8.6

6

4.8

3

-.2

3

-1.7

9

-11

.55

6.2

0

-.2

5

-1.8

6

Neu

roti

cism

- -6

.02

2.9

9

-.2

0

-2.0

1*

0.1

7

2.4

1

.01

0.0

7

-3.5

8

1.9

0

-.1

7

-1.8

8

2.1

0

2.3

2

.09

0.9

1

2.9

9

2.9

8

.11

1.0

0

Extr

aver

sion

+

-8.3

6

6.8

4

-.1

8

-1.2

2

16.9

7

5.5

1

.43

3.0

8**

2.2

1

4.3

4

.07

0.5

1

-9.0

1

5.3

0

-.2

6

-1.7

0

11.9

3

6.8

1

.28

1.7

5

Extr

aver

sion

- 9

.30

6.5

0

.20

1.4

3

-17

.16

5.2

4

-.4

4

-3.2

8***

-3.4

2

4.1

3

-.1

1

-0.8

3

-13

.48

5.0

4

-.3

9

-2.6

8**

-1.6

0

6.4

7

-.0

4

-0.2

5

Op

enn

ess

to

exp

erie

nce

+

3.6

2

6.0

6

.07

0.6

0

7.1

7

4.8

8

.17

1.4

7

14.8

4

3.8

5

.43

3.8

6***

-1.2

3

4.6

9

-.0

3

-0.2

6

-4.5

8

6.0

3

-.1

0

-0.7

6

Op

enn

ess

to

exp

erie

nce

- 0

.15

5.3

4

.00

0.0

3

-8.4

8

4.3

0

-.2

0

-1.9

7

-17

.08

3.3

9

-.4

9

-5.0

3***

-2.0

8

4.1

4

-.0

6

-0.5

0

-2.2

5

5.3

2

-.0

5

-0.4

2

Ag

reea

ble

nes

s+

0.7

4

6.1

8

.01

0.1

2

-1.5

6

4.9

8

-.0

3

-0.3

1

-0.2

4

3.9

3

-.0

1

-0.0

6

12.1

9

4.7

9

.27

2.5

4*

6.0

2

6.1

5

.11

0.9

8

Ag

reea

ble

nes

s- -0

.37

2.1

7

-.0

2

-0.1

7

-0.7

6

1.7

5

-.0

4

-0.4

3

-0.8

7

1.3

8

-.0

5

-0.6

3

-4.8

2

1.6

8

-.2

8

-2.8

6**

1.3

7

2.1

6

.06

0.6

3

Con

scie

nti

ou

snes

s+

-0.2

2

2.8

4

-.0

1

-0.0

8

1.1

2

2.2

9

.06

0.4

9

4.3

5

1.8

0

.29

2.4

1*

1.6

4

2.2

0

.10

0.7

5

-0.6

3

2.8

2

-.0

3

-0.2

2

Con

scie

nti

ou

snes

s- 0

.59

5.3

2

.01

0.1

1

-4.1

6

4.2

8

-.1

2

-0.9

7

-6.5

6

3.3

8

-.2

3

-1.9

4

6.7

6

4.1

2

.22

1.6

4

-11

.41

5.2

9

-.3

0

-2.1

6*

R

2 =

.31

R2 =

.40

R2 =

.43

R2 =

.26

R2 =

.20

R

2 a

dj

= .23

R2 a

dj

= .3

4

R2 a

dj

= .3

7

R2 a

dj

= .1

8

R2 a

dj

= .1

2

R

ad

j =

.48

R a

dj

= .58

R a

dj

= .61

R a

dj

= .43

R a

dj

= .34

K

2 =

.3

0 (

med

ium

) K

2 =

.5

0 (

larg

e)

K2 =

.5

9 (

larg

e)

K2 =

.2

2 (

med

ium

) K

2 =

.1

3 (

smal

l)

Tab

le 5

. M

ult

iple

reg

ress

ion

an

alysi

s p

red

icti

ng t

he

NE

O-P

I-R

dim

ensi

on

s.

No

te. *

p

** p

***

p

Bo

ld -

sig

nif

ican

t B

eta-

wei

ghts

. Th

e ef

fect

po

wer

fo

r m

ult

iple

lin

ear

regr

essi

on

is c

alcu

late

d a

s fo

llow

ers

(Bo

rtz

& D

öri

ng,

20

06

, p. 6

06

): K

2 =

(R2 a

dj /

(1

- R

2 a

dj)

, wh

ere

K2 ≥

0.0

2 (

smal

l

effe

ct),

K2 ≥

0.1

5 (

med

ium

eff

ect)

, K2 ≥

0.3

5 (

larg

e ef

fect

).

Page 10: Regression function and explained variance of NEO-PI-R Big ... · The NEO-PI-R was chosen because it is a well differentiated and widely used test. The NEO-PI-R is based on the German

Toggweiler (2018) 10

The raw and standardized regression coefficients of the predictors together with the standard errors

are shown in Table 5. The predictors relate, with the exception of NEO-PI-R-conscientiousness, as

expected. That is these NEO-PI-R dimensions have significant Beta-weights in both corresponding

graphological scales. In the case of extraversion, openness to experience and conscientiousness, other

scales also significantly account for explained variance: Neuroticism+ in the case of extraversion,

neuroticism+ and conscientiousness

+ in the case of openness to experience and extraversion

- in the case

of agreeableness.

The predictors accounted for about 23% of the variance in neuroticism (R2 = .31, R

2 adj = .23, R

adj = .48, K2 = medium), for about 34 % in the case of extraversion (R

2 = .40, R

2 adj = .34, R adj = .58,

K2 = large), for 37 % in the case of openness to experience (R

2 = .43, R

2 adj = .37, R adj = .61, K

2 =

large), for 18 % in the case of agreeableness (R2 = .26, R

2 adj = .18, R adj = .43, K

2 = medium) and for

12 % in the case of conscientiousness (R2 = .20, R

2 adj = .12, R adj = .34, K

2 = small). The stepwise

exclusion of handwriting signs with insufficient discriminative power (in the sense of scale

optimisation) always led to a lower extent of explained variances.

DISCUSSION

Sample

The two samples (overall sample and NEO-PI-R sample) are not representative of a general

population; they include consistently high educational qualifications (national vocational qualification,

upper secondary school, upper secondary school and higher education). However, representativeness

is not required for the current questions, since the primary interest was the method (the construction of

handwriting sign scales by means of correlation analysis) and its potential (explained variance of the

NEO-PI-R). From this point of view the homogeneous setting of the samples can even be seen as an

advantage, as it allows statements about a relatively well-defined target group of high educational

persons. Of course, these high educational level corresponds with an increased age of the sample. The

approximatly equal distribution of gender is ideal, because it leads to a balanced gender-specific

influence on the results.

Question 1: Construction of graphological scales

A first attempt (Bühler, 2015) to construct graphological scales by means of cluster analysis was

successful, since 13 scales could be constructed with high reliability in terms of Cronbach's Alpha.

Unfortunately, these scales neither correlatively, nor by means of multiple linear regressions are

significantly associated with the Big Five dimensions of the NEO-PI-R in a considerable extent. In this

respect, question 1 can be answered in such a way that it is easily possible to construct reliable

graphological scales in terms of Cronbach’s Alpha. However, the internal structure revealed by means

of cluster analysis does not relate to the Big Five personality traits. It is unclear what this structure

correlates with. Unfortunately, the sample was too small for factor analysis because that would have

been a worthwhile attempt: Scaling by means of factor analysis.

The second attempt to construct graphological scales using correlation analysis was not successful

immediately. The prerequisites for parametric analyses were not ideal, because one quarter of the

handwriting signs were not normally distributed, but nevertheless were unimodal. In these

distributions nothing can be optimized, since the handwriting signs, unlike verbal items, cannot simply

be formulated more appropriately. The method for selecting the proper handwriting signs from the

total of 234 handwriting signs consisted of constructing scales with the most significant positively and

negatively correlated characteristics with the NEO-PI-R dimensions. The discriminative power of the

handwriting signs was finally inadequate at about one third, which will of course be detrimental to the

results, however, good results under unfavourable conditions are a strong fact. The internal

consistence in terms of Cronbach’s Alpha of the graphological scales finally turned out to be not

conclusive. They range from insufficient .24 to pleasant .86. Two graphological scales (agreeableness-

and conscientiousness+) contain only one single item, therefore they are not actual scales but rather

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Toggweiler (2018) 11

single characteristics. Nevertheless, the interrater reliability of the included 68 handwriting signs must

be quite good, otherwise not one satisfying results would have been revealed by the analyses.

As answer to question 2 can be noted: The first attempt (scaling by means of cluster analysis) has

shown that it is absolutely possible to construct reliable graphological scales in terms of Cronbach’s

Alpha – we simply do not know what they correlate with; not with personality – and certainly not

directly with the dimensions of the Big Five. The second attempt (scaling by means of correlation

analysis) must also be accounted for as failed: With this method, only three reliable graphological

scales could be constructed – one third of which are inadequate in their discriminative power. Ten

reliable graphological scales would have been necessary. The value of this method is recognized if this

solution is used in the attempt to answer question 2.

Question 2: Quality of the solution

The convergent correlations of the graphological scales with the Big Five of the NEO-PI-R (Table 4)

already showed a medium validity in five out of ten cases (neuroticism+, extraversion

+, extraversion

-,

openness to experience+, and openness to experience

-), the explained variance is at least 16 %, which

corresponds to a correlation of at least .40. This finding is already a positive result and justifies the

diagnostical use of five out of ten graphological scales for the Big Five dimensions neuroticism,

extraversion and openness to experience. The result is even better with the help of linear combinations

of the graphological scales: With the primary goal of a maximizing the explained variance, all

graphological scales were in into five linear multiple regressions onto the Big Five of the NEO-PI-R.

The result was one small (conscientiousness), two medium (neuroticism, agreeableness) and two large

(extraversion, openness to experience) effects, i.e. a total of four considerable effects – agreeableness

is also present now. As a side note: Although the discriminatory power of approximately one third of

the included handwriting signs was insufficient (as far as calculable), an exclusion of these items did

not lead to an improvement of the results in any case, i.e. to an improvement of the validity of the

graphological scales respectively to an improvement of the explained variance of the NEO-PI-R. In

this respect, the numbers, apart from the explained variance of conscientiousness, express a good and

usefull quality of the solution – one may predict the Big Five with a quiet conscience in four out of

five dimensions by means of a linear combination of the defined graphological scales.

The performance of these graphological scales compared to paper-pencil tests

How considerable these reported effects are can be illustrated by the correlations between self- and

observer-assessment of the Big Five with various verbal instruments. The data in Table 6 is taken from

the manual of the NEO-PI-R (Ostendorf & Angleitner, 2004, p. 142) as well as from a recent study

from Lee and Ashton (2016, p. 8). We assume that graphological assessment is a kind of observer-

assessment.

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Toggweiler (2018) 12

Table 6. Explained variances among different self- and observer-assessments.

Big Five dimension

Neu

ro

ticis

m

Ex

tra

ver

sio

n

Op

enn

ess

to

Ex

per

ien

ce

Ag

reea

ble

nes

s

Co

nsc

ien

tio

usn

ess

NEO-PI-R self-assessment

Graphological scales1 (cf. Tab. 5) R2adj (effectsize K2) .23 (M) .34 (L) .37 (L) .18 (M) .12 (S)

NEO-PI-R observer-assessment2 r2(effectsize r) .38 (M) .40 (M) .31 (M) .30 (M) .41 (M)

BARS 179 observer-assessment2 r2(effectsize r) .32 (M) .22 (S) .14 (S) .17 (S) .27 (S)

BARS1794 self-assessment

BARS 179 observer-assessment2 r2(effectsize r) .41 (M) .30 (M) .18 (S) .14 (S) .35 (M)

NEO-PI-R observer-assessment2 r2(effectsize r) .35 (M) .20 (S) .18 (S) .16 (S) .27 (S)

HEXACO-PI-R-100 self-assessment

HEXACO-PI-R-100 self-assessment3 r2(effectsize r) .37 (M) .31 (M) .31 (M) .22 (S) .27 (S)

Note. S = Small, M = Medium, L = Large. All measures are significant at p BARS179 = Bipolar adjective-rating-scales. 1) N = 103. 2) The

correlations are based on different sample sizes between N = 83 and N = 573. 3) N = 2863. 4) Ostendorf (1990). In bold are the convergent

correlations of the graphological scales with the NEO-PI-R.

As seen from Table 5 and taken up again in Table 6, the graphological scales reach explained

variances in percentages of small (conscientiousness), medium (neuroticism, agreeableness) and large

effect sizes (extraversion, openness to experience). If one compares these numerical results with the

other values in the respective columns (i.e. the explained variance that were achieved by verbal

observer-assessment), one can see that the explained variances in the columns extraversion and

openness to experience only once respectively not at all were higher. Although neuroticism explained

by graphological scales is numerically outperformed by the other explained variances in the column, it

still maintains a medium effect size. The same applies to conscientiousness, which is also surpassed by

all other explained variances. In contrast, the graphologically explained variance of agreeableness is

approximately in the midfield of the values in the column. The balance for the graphological scales is

an approximatly middle-ranking position: Extraversion and openness to experience perform very well

and are, with both large effect sizes, winners over verbal observer-assessments. Agreeableness is in

the midfield whereas neuroticism and conscientiousness are better explained by the verbal observer-

assessment instruments. It has to be said that the explained variance calculated by means of the

adjusted R2, represents a very strict measure. Its upper limit is the (unadjusted) R

2, which reaches at

minimum the same or even much higher values than the adjusted R2. The true explained variance is

somewhere between the adjusted and the unadjusted R2 (see Table 5).

In addition, the qualifications of the authors of the NEO-PI-R (Ostendorf & Angleitner, 2004) and

NEO-FFI (Borkenau & Ostendorf, 2008) are to be taken into account, such as reported in their

manuals, concerning validity of their instruments: "The convergence of [...] the main scales can be [...]

considered as satisfactory. On average, the self-observer-agreement for the main scales [of the NEO-

PI-R] is .54 [r2 = .29] and for the facets is .47 [r

2 = .22]" (Ostendorf & Angleitner, 2004, p. 140).

Exactly the same average self-observer-agreement of R2 adj = .29, calculated by Fisher's z

transformation, is obtained with the graphological scales. Borkenau and Ostendorf (2008, p. 26) had a

similar conclusion about their NEO-FFI: "These agreements [.24 < r2 < .37] are comparatively high

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Toggweiler (2018) 13

and show that there exists [between observer- and self-assessments with the NEO-FFI] a high

agreement regarding the expression of these five personality traits [...]. The self-descriptions done by

the test persons are therefore highly realistic in terms of inter-personel agreement”. This qualification

(we achieve .12 R2 adj .37) at least partially certifies the graphological scales a "comparatively

high" agreement between observer- and self-assessment.

From all these findings, it can be concluded that the regression equations defined in Table 5 for the

Big Five dimensions neuroticism, extraversion, openness to experience and agreeableness allow a

valid prognosis of the NEO-PI-R personality traits. In other words, the validity is high enough to feel

disclosed within the Big Five dimensions. The similarities are as considerable as it is to be expected

between self- and observer-assessments - not more and not less. The two graphological scales for the

dimension conscientiousness (especially conscientiousness+) should be further optimized. Considering

that these calculations were carried out in a straightforward manner, there is certainly potential for

even better coefficients of validity.

FUTURE DIRECTIONS

The available results are very encouraging and justify the implementation of new algorithms in

GraphoPro. Nevertheless, an urgent methodological difficulty must be addressed here: Due to the high

number of correlations that were necessary to construct the graphological scales (5 * 234 = 1170

correlations), it has to be considered, that various significant correlations between handwriting signs

and NEO-PI-R may have occurred just accidentally. At a significance level of p = .05 one should

expect 59 just by chance significant relations at a total of 68 handwriting signs, which were found to

be relevant (Table 3). This uncertainty, i.e. the question of the role of chance, can be resolved in two

ways:

1. One increases the sample size from currently 103 to about 600 subjects (Rho (H1) = .20, Rho

(H0) = 0, p < .000043, Power = .80) and lowers the significance level of the correlations to p =

.05/1170 = .000043 by means of the Bonferroni correction.

2. A replication study is carried out with the 68 handwriting signs and the ten graphological

scales. On the basis of the correlations and regression values, it will be possible to evaluate the

influence of handwriting signs that were found to be relevant just by chance.

Unfortunately, the concern just described cannot be solved in this study. From these two options,

replication is certainly the more economic one. The existence of a larger sample would also allow the

use of much more elaborated methods (factor analysis or the use of structural equation modelling). As

well the unfavourable differences between the explained variance R2 and the adjusted R

2 would be

reduced due to the larger sample size. Furthermore, the inclusion of other observer ratings would be

interesting in order to test them against the graphological scales – it is a matter of competitive validity

or what graphology achieves independently of verbal diagnostic instruments.

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Toggweiler (2018) 14

REFERENCES

Borkenau, P. & Ostendorf, F. (2008). NEO-FFI. NEO-Fünf-Faktoren-Inventar nach Costa und

McCrae. Bern: Hogrefe.

Bortz, J. & Döring, N. (2006). Forschungsmethoden und Evaluation für Human- und

Sozialwissenschaftler (4. Aufl.). Heidelberg: Springer Medizin Verlag.

Bühler, E. (2015). Die Konstruktvalidität der Schriftpsychologie – Eine Validitätsuntersuchung von

Schriftmerkmalen (unpubl. Bachelor-Thesis). Zürich: Zürcher Hochschule für Angewandte

Wissenschaften ZHAW, Psychologisches Institut.

Costa, P. T. & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO PI-R) and NEO Five

Factor Inventory. Professional manual. Odessa, FL: Psychological Assessment Resources.

Digman, J. M. & Takemoto Chock, N. K. (1981). Factors in the natural language of personality: Re-

analysis, comparison, and interpretation of six major studies. Multivariate behavioral research,

16, 149-170.

Keel, B. (2016). Computeruntersützte Graphologie mit GraphoPro. Graphologie News, Juli/August

(http://graphologie-

news.net/cms/upload/archiv/Computerunterstuetzte_Graphologie_mit__GraphoPro.pdf)

Lee, K. & Ashton, M. C. (2016). Psychometric Properties of the HEXACO-100. Assessment, 0(0).

doi: 10.1177/1073191116659134.

McCrae, R. R. & Costa, P. T. (1996). Towards a new generation of personality theories: Theoretical

contexts for the five-factor model. In J. S. Wiggins (Ed.), The five-factor model of personality

(pp. 51-87). New York: Guilford Press.

McCrae, R. R. & Costa, P. T. (1999). A five-factory theory of personality. In L. A. Pervin & O. P.

John (Eds.), Handbook of personality. Theory and research. New York: Guilford Press.

Ostendorf, F. (1990). Sprache und Persönlichkeitsstruktur. Zur Validität des Fünf-Faktoren-Modells

der Persönlichkeit. Regensburg: Roderer.