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Lampiran I
Kuesioner Penelitian
KUESIONER PENELITIAN
Dengan Hormat,
Terima kasih atas kesediaan Saudara/Saudari untuk berpartisipasi untuk
mengisi dan menjawab seluruh pertanyaan yang ada dalam kuesioner ini. Penelitian
ini digunakan untuk menyusun skripsi yang berjudul “..PENGARUH CITRA
MEREK DAN KUALITAS PRODUK TERHADAP LOYALITAS KONSUMEN
MITSUBISHI PAJERO SPORT..”.
Untuk itu diharapkan para responden dapat memberikan jawaban yang
sebenar-benarnya demi membantu penelitian ini. Atas kesediaannya saya ucapkan
terima kasih, semoga penelitian ini bermanfaat bagi kita semua.
Hormat Saya,
Rinto sudiono
89
KUESIONER PENELITIAN
I. IDENTITAS RESPONDEN
Responden diharapkan menjawab pertanyaan-pertanyaan berikut dengan mengisi
bagian yang kosong atau memberi tanda (X) pada jawaban yang tersedia.
Nama :
Jenis Kelamin : a. Laki – laki
b. Perempuan
Usia : ...... tahun
Jenis pekerjaan : a. Karyawan swasta
b. Pengusaha
` c. Profesional
b. Lainnya ..................................
*apabila mempunyai pekerjaan lainnya mohon diisi pada bagian “ kolom lainnya “
Terima kasih.
PETUNJUK PENGISIAN
Anda diminta untuk memilih salah satu dari beberapa alternatif jawaban yang
tersedia dengan cara memberikan tanda silang (X) . Dalam skala ini tidak ada
penilaian benar atau salah, jawaban yang paling baik adalah yang sesuai dengan diri
anda. Adapun jawaban yang tersedia yaitu :
90
1 2 3 4
SS S TS STS
Keterangan:
SS : Sangat Setuju dengan pertanyaan
S : Setuju dengan pertanyaan
TS : Tidak Setuju dengan pertanyaan
STS : Sangat Tidak Setuju dengan pertanyaan
SELAMAT MENGERJAKAN
III . DAFTAR PERTANYAAN
No PERTANYAAN SS S TS STS
1. Merk Mitsubishi mempunyai reputasi yang baik
2. Mitsubishi merupakan merek yang sangat terkenal didunia otomotif
3. Mitsubishi sudah lama Mengikuti ajang balap Rally Dunia.
4. Mitsubishi sangat identik dengan mobil yang kencang larinya.
5. Merk Mitsubishi dikenal diseluruh dunia.
6. Mitsubishi pajero sport terkenal tangguh dimedan off road
91
Sumber : Anca.E.Cretu and Roderick J.Brondie “The influence brand image and company reputation where manufactures market to small firms: A customer value perspective”.mei 2005
7. Saya akan merekomendasikan produk mitsubishi pajero sport ke teman saya
8. Saya akan merekomendasikan produk pajero sport ke saudara saya
9. Apabila saya akan mengganti mobil saya akan membeli pajero sport.
10. Saya merasa suka dengan produk mitsubishi pajero sport.
11. Mitsubishi Pajero sport mempunyai purna jual yang bagus (resale value) yang bagus .
12. Mitsubishi pajero sport merupakan produk yang bagus
13. Sales mitsubishi memberikan penjelasan yang baik mengenai informasi produk pajero sport.
14. Mitsubishi pajero sport menggunakan mesin diesel yang irit.
15. Mitsubishi pajero mudah dalam perawatan
92
LAMPIRAN II
Data Final Skala pernyataan
93
Lampiran 3. Uji validitas instrumen Citra Merek
Correlation Matrixa
CIM1 CIM2 CIM3 CIM4 CIM5 CIM6
Correlation CIM1 1.000 .262 .263 .342 .208 .273
CIM2 .262 1.000 .371 .366 .108 .250
CIM3 .263 .371 1.000 .310 .213 .297
CIM4 .342 .366 .310 1.000 .409 .218
CIM5 .208 .108 .213 .409 1.000 .299
CIM6 .273 .250 .297 .218 .299 1.000
Sig. (1-tailed) CIM1 .012 .011 .001 .037 .009
CIM2 .012 .001 .001 .178 .015
CIM3 .011 .001 .003 .033 .005
CIM4 .001 .001 .003 .000 .030
CIM5 .037 .178 .033 .000 .005
CIM6 .009 .015 .005 .030 .005
a. Determinant = .401
Inverse of Correlation Matrix
CIM1 CIM2 CIM3 CIM4 CIM5 CIM6
CIM1 1.220 -.120 -.125 -.275 -.044 -.193
CIM2 -.120 1.310 -.326 -.362 .150 -.164
CIM3 -.125 -.326 1.281 -.155 -.087 -.205
CIM4 -.275 -.362 -.155 1.463 -.480 .037
CIM5 -.044 .150 -.087 -.480 1.292 -.281
CIM6 -.193 -.164 -.205 .037 -.281 1.230
94
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .729
Bartlett's Test of Sphericity Approx. Chi-Square 65.058
Df 15
Sig. .000
Anti-image Matrices
CIM1 CIM2 CIM3 CIM4 CIM5 CIM6
Anti-image Covariance CIM1 .820 -.075 -.080 -.154 -.028 -.129
CIM2 -.075 .764 -.194 -.189 .089 -.102
CIM3 -.080 -.194 .780 -.083 -.053 -.130
CIM4 -.154 -.189 -.083 .683 -.254 .020
CIM5 -.028 .089 -.053 -.254 .774 -.177
CIM6 -.129 -.102 -.130 .020 -.177 .813
Anti-image Correlation CIM1 .810a -.095 -.100 -.206 -.035 -.157
CIM2 -.095 .708a -.252 -.262 .115 -.129
CIM3 -.100 -.252 .788a -.113 -.068 -.163
CIM4 -.206 -.262 -.113 .695a -.349 .027
CIM5 -.035 .115 -.068 -.349 .652a -.223
CIM6 -.157 -.129 -.163 .027 -.223 .753a
a. Measures of Sampling Adequacy(MSA)
95
Communalities
Initial Extraction
CIM1 1.000 .379
CIM2 1.000 .391
CIM3 1.000 .427
CIM4 1.000 .515
CIM5 1.000 .331
CIM6 1.000 .363
Extraction Method: Principal
Component Analysis.
Total Variance Explained
Compo
nent
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 2.405 40.083 40.083 2.405 40.083 40.083
2 .947 15.776 55.859
3 .805 13.424 69.283
4 .753 12.549 81.833
5 .627 10.449 92.281
6 .463 7.719 100.000
Extraction Method: Principal Component Analysis.
96
Component Matrixa
Component
1
CIM1 .615
CIM2 .626
CIM3 .653
CIM4 .717
CIM5 .575
CIM6 .602
Extraction Method:
Principal Component
Analysis.
a. 1 components
extracted.
Reproduced Correlations
CIM1 CIM2 CIM3 CIM4 CIM5 CIM6
Reproduced Correlation CIM1 .379a .385 .402 .442 .354 .371
CIM2 .385 .391a .409 .449 .360 .377
CIM3 .402 .409 .427a .469 .376 .393
CIM4 .442 .449 .469 .515a .413 .432
CIM5 .354 .360 .376 .413 .331a .346
CIM6 .371 .377 .393 .432 .346 .363a
Residualb CIM1 -.123 -.139 -.100 -.146 -.098
CIM2 -.123 -.037 -.083 -.252 -.127
CIM3 -.139 -.037 -.159 -.163 -.097
CIM4 -.100 -.083 -.159 -.003 -.214
CIM5 -.146 -.252 -.163 -.003 -.048
CIM6 -.098 -.127 -.097 -.214 -.048
Extraction Method: Principal Component Analysis.
a. Reproduced communalities
97
Component Matrixa
Component
1
CIM1 .615
CIM2 .626
CIM3 .653
CIM4 .717
CIM5 .575
CIM6 .602
Extraction Method:
Principal Component
Analysis.
b. Residuals are computed between observed and reproduced correlations. There are 12 (80.0%) nonredundant
residuals with absolute values greater than 0.05.
Lampiran 4. Uji validitas instrumen Kualitas Produk
Correlation Matrixa
KUP1 KUP2 KUP3 KUP4 KUP5
Correlation KUP1 1.000 .520 .573 .425 .511
KUP2 .520 1.000 .659 .624 .421
KUP3 .573 .659 1.000 .680 .542
KUP4 .425 .624 .680 1.000 .539
KUP5 .511 .421 .542 .539 1.000
Sig. (1-tailed) KUP1 .000 .000 .000 .000
KUP2 .000 .000 .000 .000
KUP3 .000 .000 .000 .000
KUP4 .000 .000 .000 .000
KUP5 .000 .000 .000 .000
a. Determinant = .104
98
Inverse of Correlation Matrix
KUP1 KUP2 KUP3 KUP4 KUP5
KUP1 1.720 -.434 -.559 .187 -.495
KUP2 -.434 2.078 -.708 -.687 .102
KUP3 -.559 -.708 2.569 -.889 -.329
KUP4 .187 -.687 -.889 2.242 -.533
KUP5 -.495 .102 -.329 -.533 1.676
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .825
Bartlett's Test of Sphericity Approx. Chi-Square 162.064
df 10
Sig. .000
Anti-image Matrices
KUP1 KUP2 KUP3 KUP4 KUP5
Anti-image Covariance KUP1 .582 -.122 -.126 .049 -.172
KUP2 -.122 .481 -.133 -.147 .029
KUP3 -.126 -.133 .389 -.154 -.076
KUP4 .049 -.147 -.154 .446 -.142
KUP5 -.172 .029 -.076 -.142 .597
Anti-image Correlation KUP1 .827a -.230 -.266 .095 -.292
KUP2 -.230 .835a -.306 -.318 .055
KUP3 -.266 -.306 .823a -.371 -.159
KUP4 .095 -.318 -.371 .804a -.275
KUP5 -.292 .055 -.159 -.275 .844a
a. Measures of Sampling Adequacy(MSA)
99
Communalities
Initial Extraction
KUP1 1.000 .560
KUP2 1.000 .657
KUP3 1.000 .760
KUP4 1.000 .678
KUP5 1.000 .552
Extraction Method: Principal
Component Analysis.
Total Variance Explained
Compo
nent
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 3.207 64.148 64.148 3.207 64.148 64.148
2 .628 12.553 76.701
3 .553 11.066 87.767
4 .327 6.546 94.313
5 .284 5.687 100.000
Extraction Method: Principal Component Analysis.
Component Matrixa
Component
1
KUP1 .748
KUP2 .811
KUP3 .872
KUP4 .823
KUP5 .743
Extraction Method:
Principal Component
Analysis.
100
Anti-image Matrices
KUP1 KUP2 KUP3 KUP4 KUP5
Anti-image Covariance KUP1 .582 -.122 -.126 .049 -.172
KUP2 -.122 .481 -.133 -.147 .029
KUP3 -.126 -.133 .389 -.154 -.076
KUP4 .049 -.147 -.154 .446 -.142
KUP5 -.172 .029 -.076 -.142 .597
Anti-image Correlation KUP1 .827a -.230 -.266 .095 -.292
KUP2 -.230 .835a -.306 -.318 .055
KUP3 -.266 -.306 .823a -.371 -.159
KUP4 .095 -.318 -.371 .804a -.275
KUP5 -.292 .055 -.159 -.275 .844a
a. 1 components
extracted.
Reproduced Correlations
KUP1 KUP2 KUP3 KUP4 KUP5
Reproduced Correlation KUP1 .560a .606 .652 .616 .556
KUP2 .606 .657a .707 .668 .602
KUP3 .652 .707 .760a .718 .648
KUP4 .616 .668 .718 .678a .612
KUP5 .556 .602 .648 .612 .552a
Residualb KUP1 -.087 -.079 -.191 -.044
KUP2 -.087 -.048 -.043 -.182
KUP3 -.079 -.048 -.038 -.106
KUP4 -.191 -.043 -.038 -.073
KUP5 -.044 -.182 -.106 -.073
Extraction Method: Principal Component Analysis.
a. Reproduced communalities
101
Anti-image Matrices
KUP1 KUP2 KUP3 KUP4 KUP5
Anti-image Covariance KUP1 .582 -.122 -.126 .049 -.172
KUP2 -.122 .481 -.133 -.147 .029
KUP3 -.126 -.133 .389 -.154 -.076
KUP4 .049 -.147 -.154 .446 -.142
KUP5 -.172 .029 -.076 -.142 .597
Anti-image Correlation KUP1 .827a -.230 -.266 .095 -.292
KUP2 -.230 .835a -.306 -.318 .055
KUP3 -.266 -.306 .823a -.371 -.159
KUP4 .095 -.318 -.371 .804a -.275
KUP5 -.292 .055 -.159 -.275 .844a
b. Residuals are computed between observed and reproduced correlations. There are 6 (60.0%)
nonredundant residuals with absolute values greater than 0.05.
Lampiran 5. Uji validitas instrumen Loyalitas Konsumen
Correlation Matrixa
LOP1 LOP2 LOP3 LOP4
Correlation LOP1 1.000 .815 .604 .622
LOP2 .815 1.000 .625 .597
LOP3 .604 .625 1.000 .666
LOP4 .622 .597 .666 1.000
Sig. (1-tailed) LOP1 .000 .000 .000
LOP2 .000 .000 .000
LOP3 .000 .000 .000
LOP4 .000 .000 .000
a. Determinant = .094
102
Inverse of Correlation Matrix
LOP1 LOP2 LOP3 LOP4
LOP1 3.279 -2.179 -.232 -.585
LOP2 -2.179 3.262 -.588 -.200
LOP3 -.232 -.588 2.115 -.914
LOP4 -.585 -.200 -.914 2.091
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .777
Bartlett's Test of Sphericity Approx. Chi-Square 170.161
df 6
Sig. .000
Anti-image Matrices
LOP1 LOP2 LOP3 LOP4
Anti-image Covariance LOP1 .305 -.204 -.033 -.085
LOP2 -.204 .307 -.085 -.029
LOP3 -.033 -.085 .473 -.207
LOP4 -.085 -.029 -.207 .478
Anti-image Correlation LOP1 .739a -.666 -.088 -.223
LOP2 -.666 .738a -.224 -.077
LOP3 -.088 -.224 .829a -.434
LOP4 -.223 -.077 -.434 .829a
a. Measures of Sampling Adequacy(MSA)
103
Communalities
Initial Extraction
LOP1 1.000 .788
LOP2 1.000 .785
LOP3 1.000 .700
LOP4 1.000 .693
Extraction Method: Principal
Component Analysis.
Total Variance Explained
Compo
nent
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 2.966 74.157 74.157 2.966 74.157 74.157
2 .514 12.861 87.019
3 .338 8.439 95.458
4 .182 4.542 100.000
Extraction Method: Principal Component Analysis.
Component Matrixa
Component
1
LOP1 .888
LOP2 .886
LOP3 .836
LOP4 .833
Extraction Method:
Principal Component
Analysis.
a. 1 components
extracted.
104
Reproduced Correlations
LOP1 LOP2 LOP3 LOP4
Reproduced Correlation LOP1 .788a .787 .742 .739
LOP2 .787 .785a .741 .738
LOP3 .742 .741 .700a .696
LOP4 .739 .738 .696 .693a
Residualb LOP1 .028 -.138 -.117
LOP2 .028 -.117 -.141
LOP3 -.138 -.117 -.031
LOP4 -.117 -.141 -.031
Extraction Method: Principal Component Analysis.
a. Reproduced communalities
b. Residuals are computed between observed and reproduced correlations. There are 4
(66.0%) nonredundant residuals with absolute values greater than 0.05.
Lampiran 6. Uji reliabilitas instrumen Citra Merek
Case Processing Summary
N %
Cases Valid 75 100.0
Excludeda 0 .0
Total 75 100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's
Alpha N of Items
105
Reliability Statistics
Cronbach's
Alpha N of Items
.698 6
Lampiran 7. Uji reliabilitas instrumen Kualitas Produk
Case Processing Summary
N %
Cases Valid 75 100.0
Excludeda 0 .0
Total 75 100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's
Alpha N of Items
.859 5
Lampiran 8. Uji reliabilitas instrumen Loyalitas Konsumen
Case Processing Summary
N %
Cases Valid 75 100.0
Excludeda 0 .0
Total 75 100.0
a. Listwise deletion based on all variables in the
procedure.
106
Reliability Statistics
Cronbach's
Alpha N of Items
.884 4
Lampiran 9. Output Analisis Structural Equation Modelling (SEM) DATE: 6/14/2014 TIME: 12:22 L I S R E L 8.51 BY Karl G. Jöreskog & Dag Sörbom This program is published exclusively by Scientific Software International, Inc. 7383 N. Lincoln Avenue, Suite 100 Lincolnwood, IL 60712, U.S.A. Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140 Copyright by Scientific Software International, Inc., 1981-2001 Use of this program is subject to the terms specified in the Universal Copyright Convention. Website: www.ssicentral.com The following lines were read from file E:\SKripsi Rinto\rinto data lisrel.LS8: raw data from file DATARINTO.psf latent variables: CIM KUP LOP relationships: CIM1 = CIM CIM2 = CIM CIM3 = CIM CIM4 = CIM !CIM5 = CIM !CIM6 = CIM KUP1 = KUP KUP2 = KUP KUP3 = KUP
107
KUP4 = KUP KUP5 = KUP LOP1 = LOP LOP2 = LOP LOP3 = LOP LOP4 = LOP CIM = KUP LOP = CIM KUP options: SC path diagram end of problem Sample Size = 75 Covariance Matrix CIM1 CIM2 CIM3 CIM4 LOP1 LOP2 -------- -------- -------- -------- -------- -------- CIM1 0.19 CIM2 0.05 0.23 CIM3 0.06 0.09 0.25 CIM4 0.08 0.09 0.08 0.30 LOP1 0.02 0.06 0.03 0.05 1.07 LOP2 0.02 0.02 -0.02 0.02 0.87 1.06 LOP3 0.10 0.02 0.00 -0.01 0.59 0.61 LOP4 0.07 0.06 0.14 0.15 0.61 0.58 KUP1 - - 0.02 0.05 0.04 0.13 0.00 KUP2 0.04 -0.09 0.02 0.08 -0.02 0.01 KUP3 0.05 -0.03 0.02 0.09 0.08 0.03 KUP4 -0.03 -0.07 -0.08 0.08 -0.06 -0.13 KUP5 0.02 -0.06 0.03 0.08 0.16 0.14 Covariance Matrix LOP3 LOP4 KUP1 KUP2 KUP3 KUP4 -------- -------- -------- -------- -------- -------- LOP3 0.90 LOP4 0.60 0.90 KUP1 0.19 0.20 0.77 KUP2 0.13 0.20 0.44 0.95 KUP3 0.18 0.19 0.44 0.57 0.78 KUP4 0.09 0.07 0.34 0.55 0.54 0.82 KUP5 0.15 0.28 0.41 0.37 0.44 0.45 Covariance Matrix
108
KUP5 -------- KUP5 0.83 Number of Iterations = 15 LISREL Estimates (Maximum Likelihood) Measurement Equations CIM1 = 0.22*CIM, Errorvar.= 0.14 , R² = 0.25 (0.028) 5.03 CIM2 = 0.28*CIM, Errorvar.= 0.15 , R² = 0.35 (0.10) (0.034) 2.83 4.28 CIM3 = 0.27*CIM, Errorvar.= 0.17 , R² = 0.30 (0.099) (0.037) 2.74 4.70 CIM4 = 0.34*CIM, Errorvar.= 0.18 , R² = 0.39 (0.12) (0.045) 2.85 4.00 LOP1 = 0.93*LOP, Errorvar.= 0.21 , R² = 0.80 (0.065) 3.29 LOP2 = 0.91*LOP, Errorvar.= 0.23 , R² = 0.79 (0.093) (0.065) 9.84 3.48 LOP3 = 0.68*LOP, Errorvar.= 0.43 , R² = 0.52 (0.094) (0.080) 7.27 5.39 LOP4 = 0.68*LOP, Errorvar.= 0.43 , R² = 0.52 (0.094) (0.081) 7.26 5.39 KUP1 = 0.57*KUP, Errorvar.= 0.44 , R² = 0.43
109
(0.095) (0.080) 6.00 5.45 KUP2 = 0.74*KUP, Errorvar.= 0.40 , R² = 0.58 (0.10) (0.082) 7.35 4.89 KUP3 = 0.76*KUP, Errorvar.= 0.19 , R² = 0.75 (0.086) (0.055) 8.86 3.49 KUP4 = 0.71*KUP, Errorvar.= 0.32 , R² = 0.61 (0.093) (0.068) 7.58 4.74 KUP5 = 0.59*KUP, Errorvar.= 0.49 , R² = 0.42 (0.100) (0.088) 5.90 5.48 Structural Equations CIM = 0.072*KUP, Errorvar.= 0.99 , R² = 0.0051 (0.15) (0.55) 0.47 1.80 LOP = 0.14*CIM + 0.098*KUP, Errorvar.= 0.97 , R² = 0.032 (0.15) (0.13) (0.21) 0.93 0.76 4.68 Reduced Form Equations CIM = 0.072*KUP, Errorvar.= 0.99, R² = 0.0051 (0.15) 0.47 LOP = 0.11*KUP, Errorvar.= 0.99, R² = 0.012 (0.13) 0.84 Correlation Matrix of Independent Variables KUP -------- 1.00
110
Covariance Matrix of Latent Variables CIM LOP KUP -------- -------- -------- CIM 1.00 LOP 0.15 1.00 KUP 0.07 0.11 1.00 Goodness of Fit Statistics Degrees of Freedom = 62 Minimum Fit Function Chi-Square = 124.99 (P = 0.00) Normal Theory Weighted Least Squares Chi-Square = 98.68 (P = 0.0021) Estimated Non-centrality Parameter (NCP) = 36.68 90 Percent Confidence Interval for NCP = (13.50 ; 67.77) Minimum Fit Function Value = 1.69 Population Discrepancy Function Value (F0) = 0.50 90 Percent Confidence Interval for F0 = (0.18 ; 0.92) Root Mean Square Error of Approximation (RMSEA) = 0.089 90 Percent Confidence Interval for RMSEA = (0.054 ; 0.12) P-Value for Test of Close Fit (RMSEA < 0.05) = 0.035 Expected Cross-Validation Index (ECVI) = 2.12 90 Percent Confidence Interval for ECVI = (1.80 ; 2.54) ECVI for Saturated Model = 2.46 ECVI for Independence Model = 6.94 Chi-Square for Independence Model with 78 Degrees of Freedom = 487.67 Independence AIC = 513.67 Model AIC = 156.68 Saturated AIC = 182.00 Independence CAIC = 556.80 Model CAIC = 252.88 Saturated CAIC = 483.89 Normed Fit Index (NFI) = 0.74 Non-Normed Fit Index (NNFI) = 0.81 Parsimony Normed Fit Index (PNFI) = 0.59 Comparative Fit Index (CFI) = 0.85 Incremental Fit Index (IFI) = 0.85 Relative Fit Index (RFI) = 0.68 Critical N (CN) = 54.76 Root Mean Square Residual (RMR) = 0.067 Standardized RMR = 0.098
111
Goodness of Fit Index (GFI) = 0.83 Adjusted Goodness of Fit Index (AGFI) = 0.75 Parsimony Goodness of Fit Index (PGFI) = 0.57 The Modification Indices Suggest to Add the Path to from Decrease in Chi-Square New Estimate LOP4 CIM 9.5 0.31 The Modification Indices Suggest to Add an Error Covariance Between and Decrease in Chi-Square New Estimate LOP2 LOP1 14.5 0.40 LOP4 LOP3 9.4 0.18 Standardized Solution LAMBDA-Y CIM LOP -------- -------- CIM1 0.22 - - CIM2 0.28 - - CIM3 0.27 - - CIM4 0.34 - - LOP1 - - 0.93 LOP2 - - 0.91 LOP3 - - 0.68 LOP4 - - 0.68 LAMBDA-X KUP -------- KUP1 0.57 KUP2 0.74 KUP3 0.76 KUP4 0.71 KUP5 0.59 BETA CIM LOP -------- -------- CIM - - - - LOP 0.14 - - GAMMA KUP --------
112
CIM 0.07 LOP 0.10 Correlation Matrix of ETA and KSI CIM LOP KUP -------- -------- -------- CIM 1.00 LOP 0.15 1.00 KUP 0.07 0.11 1.00 PSI Note: This matrix is diagonal. CIM LOP -------- -------- 0.99 0.97 Regression Matrix ETA on KSI (Standardized) KUP -------- CIM 0.07 LOP 0.11 Completely Standardized Solution LAMBDA-Y CIM LOP -------- -------- CIM1 0.50 - - CIM2 0.60 - - CIM3 0.55 - - CIM4 0.62 - - LOP1 - - 0.89 LOP2 - - 0.89 LOP3 - - 0.72 LOP4 - - 0.72 LAMBDA-X KUP -------- KUP1 0.65 KUP2 0.76 KUP3 0.87 KUP4 0.78 KUP5 0.65
113
BETA CIM LOP -------- -------- CIM - - - - LOP 0.14 - - GAMMA KUP -------- CIM 0.07 LOP 0.10 Correlation Matrix of ETA and KSI CIM LOP KUP -------- -------- -------- CIM 1.00 LOP 0.15 1.00 KUP 0.07 0.11 1.00 PSI Note: This matrix is diagonal. CIM LOP -------- -------- 0.99 0.97 THETA-EPS CIM1 CIM2 CIM3 CIM4 LOP1 LOP2 -------- -------- -------- -------- -------- -------- 0.75 0.65 0.70 0.61 0.20 0.21 THETA-EPS LOP3 LOP4 -------- -------- 0.48 0.48 THETA-DELTA KUP1 KUP2 KUP3 KUP4 KUP5 -------- -------- -------- -------- -------- 0.57 0.42 0.25 0.39 0.58 Regression Matrix ETA on KSI (Standardized) KUP
114
-------- CIM 0.07 LOP 0.11 Time used: 0.062 Seconds
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