Differential Item Functioning (DIF) Etnis pada Big Five Inventory (BFI) versi Adaptasi Fakultas Psikologi Universitas Sumatera Utara

KATA PENGANTAR

  Dengan hormat, Sehubungan dengan persyaratan penyelesaian pendidikan sarjana di

Fakultas Psikologi USU, peneliti bermaksud untuk melakukan penelitian di

bidang Psikometri. Untuk itu, peneliti membutuhkan sejumlah data yang dapat

diperoleh dengan adanya kerjasama dari saudara/i dalam mengisi skala ini.

  Peneliti sangat mengharapkan saudara/i lebih dahulu memperhatikan

petunjuk tersebut dengan sebelum mengisi skala ini. Ketika selesai mengerjakan,

periksalah kembali jawaban saudara/i agar tidak ada pernyataan yang terlewatkan.

  Kesediaan saudara/i untuk mengisi skala ini merupakan bantuan yang sangat berharga untuk keberhasilan penelitian ini. Untuk itu, peneliti mengucapkan terima kasih.

  Hormat Kami, Peneliti

BIG FIVE INVENTORY

  

Berikut adalah beberapa karakteristik yang mungkin atau mungkin tidak

menggambarkan diri anda. Misalnya pada pernyataan “saya adalah seseorang

yang senang menghabiskan waktu dengan orang lain”, maka tuliskan nomor di

samping pernyataan yang menyatakan anda setuju atau tidak setuju dengan

pernyataan tersebut. 1 = Sangat Tidak Setuju 2 = Tidak Setuju 3 = Netral 4 = Setuju 5 = Sangat Setuju

Saya adalah seseorang (yang)… 1. _______ Suka mengobrol

  2. _______ Cenderung mencari kesalahan orang lain. 3. _______ Mengerjakan tugas sampai selesai. 4. _______ Mudah merasa tertekan dan sedih. 5. _______ Memiliki ide-ide yang inovatif. 6. _______ Suka menyendiri. 7. _______ Senang membantu dan tidak egois. 8. _______ Terkadang ceroboh. 9. _______ Dapat menghadapi situasi stress dengan baik. 10. _______ Memiliki rasa ingin tahu terhadap banyak hal. 11. _______ Penuh semangat. 12. _______ Tidak takut berargumentasi dengan orang lain. 13. _______ Pekerja yang dapat diandalkan. 14. _______ Mudah merasa cemas. 15. _______ Cerdas dan suka berpikir. 16. _______ Penuh antusiasme.

  17. _______ Mudah memaafkan. 18. _______ Cenderung tidak teratur atau berantakan. 19. _______ Pencemas. 20. _______ Memiliki imajinasi yang tinggi 21. _______ Cenderung pendiam 22. _______ Mudah mempercayai orang lain 23. _______ Cenderung pemalas 24. _______ Secara emosional stabil, tidak mudah tersinggung 25. _______ Mudah menemukan suatu ide baru.

  26. _______ Percaya diri. 27. _______ Cenderung menjaga jarak dengan orang lain. 28. _______ Mampu bertahan hingga suatu tugas selesai. 29. _______ Suasana hati mudah berubah. 30. _______ Menghargai hal-hal yang indah dan berseni. 31. _______ Terkadang pemalu. 32. _______ Baik dan perhatian hampir terhadap setiap orang. 33. _______ Melakukan sesuatu dengan efisien. 34. _______ Tetap tenang pada situasi yang menegangkan. 35. _______ Lebih menyukai pekerjaan yang rutin. 36. _______ Santai dan mudah bergaul. 37. _______ Terkadang kasar kepada orang lain. 38. _______ Dapat membuat rencana dan menjalankannya. 39. _______ Mudah merasa cemas. 40. _______ Mempertimbangkan gagasan-gagasan yang ada.

  41. _______ Kurang memiliki ketertarikan terhadap seni. 42. _______ Senang bekerjasama dengan orang lain. 43. _______ Perhatiannya mudah terganggu. 44. _______ Memiliki kemampuan yang baik dalam seni, music atau sastra.

Hasil Analisis Regresi Logistik

  Aitem1

Matrix

  [DataSet14] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Extraversion\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 8.00 2.45 97.55 2.00 24.00 7.34 90.21

  3.00 103.00 31.50 58.72 4.00 119.00 36.39 22.32 5.00 73.00 22.32 .00

  Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 19.7095 2.4403

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 882.224
• 2 Log-Likelihood of full Model: 856.242 LR-statistic Chisqu. DF Prob. %-Reduct 25.982 1.000 .000 .029 Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .218682 .043731 5.000660 .000001 1.244435 1.705155 Const.1 -.498955 .900284 -.554220 .579429 .607165 1.000000

  Const.2 -1.989168 .853654 -2.330179 .019797 .136809 1.000000 Const.3 -3.942166 .864450 -4.560318 .000005 .019406 1.000000 Const.4 -5.635691 .893519 -6.307295 .000000 .003568 1.000000 Results assuming a latent continuous variable

  R-Square (%):

  7.97 Standardized regression weights of the latent variable: total .2823

• END MATRIX -----

Matrix

  [DataSet14] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Extraversion\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item

  Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 8.00 2.45 97.55 2.00 24.00 7.34 90.21 3.00 103.00 31.50 58.72 4.00 119.00 36.39 22.32 5.00 73.00 22.32 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 19.7095 2.4403 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 882.224
• 2 Log-Likelihood of full Model: 817.677 LR-statistic Chisqu. DF Prob. %-Reduct 64.547 2.000 .000 .073 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S)
total .217038 .044673 4.858417 .000001 1.242391 1.698328 grp 1.308867 .216287 6.051525 .000000 3.701976 1.924276 Const.1 -2.180297 .956533 -2.279374 .022645 .113008 1.000000 Const.2 -3.705182 .917478 -4.038441 .000054 .024596 1.000000 Const.3 -5.807024 .944285 -6.149649 .000000 .003006 1.000000 Const.4 -7.661101 .985291 -7.775469 .000000 .000471 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  18.86 Standardized regression weights of the latent variable: total .2630 grp .3251

• END MATRIX -----

Matrix

  [DataSet14] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Extraversion\data.sav Run MATRIX procedure:

  LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 8.00 2.45 97.55 2.00 24.00 7.34 90.21

  3.00 103.00 31.50 58.72 4.00 119.00 36.39 22.32 5.00 73.00 22.32 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 19.7095 2.4403 grp 1.4740 .5001 int1.1 29.1498 10.7509

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only:

  882.224

• 2 Log-Likelihood of full Model: 815.658 LR-statistic Chisqu. DF Prob. %-Reduct 66.565 3.000 .000 .075 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .393903 .132750 2.967261 .003005 1.482757 2.614975 grp 3.823268 1.785102 2.141765 .032212 45.753497 6.766438 int1.1 -.126994 .089363 -1.421111 .155285 .880739 .255304

  Const.1 -5.636815 2.622129 -2.149709 .031578 .003564 1.000000 Const.2 -7.174384 2.617685 -2.740737 .006130 .000766 1.000000 Const.3 -9.306909 2.651090 -3.510597 .000447 .000091 1.000000 Const.4 -11.157840 2.665669 -4.185756 .000028 .000014 1.000000 Results assuming a latent continuous variable

  R-Square (%):

  19.54 Standardized regression weights of the latent variable: total .4754 grp .9456 int1.1 -.6752

• END MATRIX -----

  Aitem 2

Matrix

  [DataSet13] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Conscientiousness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ********************

  Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 53.00 16.21 83.79 2.00 149.00 45.57 38.23 3.00 75.00 22.94 15.29 4.00 41.00 12.54 2.75 5.00 9.00 2.75 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 21.8043 2.9782

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 882.921
• 2 Log-Likelihood of full Model: 788.475 LR-statistic Chisqu. DF Prob. %-Reduct 94.445 1.000 .000 .107 Estimations, standard errors, and effects

  Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .369195 .040652 9.081770 .000000 1.446569 3.002747 Const.1 -6.023717 .844968 -7.128926 .000000 .002421 1.000000 Const.2 -8.605489 .912690 -9.428711 .000000 .000183 1.000000 Const.3 -10.119867 .959510 -10.546909 .000000 .000040 1.000000 Const.4 -12.187274 1.041476 -11.701921 .000000 .000005 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  26.87 Standardized regression weights of the latent variable: total .5184

• END MATRIX -----

  Matrix

  [DataSet13] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Conscientiousness\data.sav

  Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 53.00 16.21 83.79 2.00 149.00 45.57 38.23

  3.00 75.00 22.94 15.29 4.00 41.00 12.54 2.75 5.00 9.00 2.75 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 21.8043 2.9782 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 882.921
• 2 Log-Likelihood of full Model: 772.660 LR-statistic Chisqu. DF Prob. %-Reduct 110.261 2.000 .000 .125 Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .385928 .041154 9.377661 .000000 1.470979 3.156185 grp -.841260 .213841 -3.934052 .000084 .431167 .656584 Const.1 -5.079085 .875199 -5.803346 .000000

  .006226 1.000000 Const.2 -7.715930 .933855 -8.262452 .000000 .000446 1.000000 Const.3 -9.301238 .978630 -9.504350 .000000 .000091 1.000000 Const.4 -11.461526 1.061026 -10.802309 .000000 .000011 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  31.42 Standardized regression weights of the latent variable: total .5248 grp -.1921

• END MATRIX -----

Matrix

  [DataSet13] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Conscientiousness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 53.00 16.21 83.79 2.00 149.00 45.57 38.23

  3.00 75.00 22.94 15.29 4.00 41.00 12.54 2.75 5.00 9.00 2.75 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 21.8043 2.9782 grp 1.4740 .5001 int1.1 32.1254 11.7450

• Estimation Section ******************** Running Iteration No.:

  1

  Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 882.921
• 2 Log-Likelihood of full Model: 770.587 LR-statistic Chisqu. DF Prob. %-Reduct 112.333 3.000 .000 .127

  Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .538587 .114922 4.686523 .000003 1.713584 4.972925 grp 1.451076 1.608894 .901909 .367105 4.267705 2.066110 int1.1 -.104650 .072894 -1.435649 .151102 .900640 .292553

  Const.1 -8.422759 2.503687 -3.364142 .000768 .000220 1.000000 Const.2 -11.040407 2.515267 -4.389358 .000011 .000016 1.000000 Const.3 -12.654125 2.552681 -4.957190 .000001 .000003 1.000000 Const.4 -14.865297 2.623438 -5.666341 .000000 .000000 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  32.10 Standardized regression weights of the latent variable: total .7287 grp .3297 int1.1 -.5584

• END MATRIX -----

  Aitem 3

Matrix

  [DataSet13] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Conscientiousness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ********************

  Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 2.00 .61 99.39 2.00 20.00 6.12 93.27 3.00 72.00 22.02 71.25 4.00 169.00 51.68 19.57 5.00 64.00 19.57 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 21.8043 2.9782

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3

  ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 781.949
• 2 Log-Likelihood of full Model: 780.420 LR-statistic Chisqu. DF Prob. %-Reduct 1.529 1.000 .216 .002 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .045359 .036685 1.236451 .216291 1.046404 1.144638

  Const.1 4.110029 1.061040 3.873586 .000107 60.948458 1.000000 Const.2 1.646506 .821602 2.004018 .045068 5.188817 1.000000 Const.3 -.076793 .803746 -.095543 .923883 .926082 1.000000 Const.4 -2.405115 .816010 -2.947410 .003204 .090255 1.000000 Results assuming a latent continuous variable

• R-Square (%): .55 Standardized regression weights of the latent variable: total .0743
• END MATRIX -----

Matrix

  [DataSet13] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Conscientiousness\data.sav Run MATRIX procedure:

  LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 2.00 .61 99.39 2.00 20.00 6.12 93.27

  3.00 72.00 22.02 71.25 4.00 169.00 51.68 19.57 5.00 64.00 19.57 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 21.8043 2.9782 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 781.949
• 2 Log-Likelihood of full Model: 780.396 LR-statistic Chisqu. DF Prob. %-Reduct 1.553 2.000 .460 .002

  Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .045481 .036683 1.239847 .215032 1.046531 1.145053 grp .032038 .208832 .153415 .878071 1.032557 1.016151 Const.1 4.060122 1.109623 3.659010 .000253

  57.981357 1.000000 Const.2 1.596444 .883851 1.806237 .070881 4.935451 1.000000 Const.3 -.127005 .867644 -.146379 .883622 .880729 1.000000 Const.4 -2.455399 .879382 -2.792187 .005235 .085829 1.000000 Results assuming a latent continuous variable

• R-Square (%): .56 Standardized regression weights of the latent variable: total .0745 grp .0088
• END MATRIX -----

Matrix

  [DataSet13] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Conscientiousness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 2.00 .61 99.39

  2.00 20.00 6.12 93.27 3.00 72.00 22.02 71.25 4.00 169.00 51.68 19.57 5.00 64.00 19.57 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 21.8043 2.9782 grp 1.4740 .5001 int1.1 32.1254 11.7450

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 781.949
• 2 Log-Likelihood of full Model: 767.489 LR-statistic Chisqu. DF Prob. %-Reduct 14.460 3.000 .002 .018 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total -.339645 .113635 -2.988912 .002800 .712023 .363665 grp -5.720304 1.624858 -3.520495 .000431 .003279 .057231 int1.1 .264376 .074024 3.571490 .000355 1.302618 22.311271

  Const.1 12.513264 2.622816 4.770928 .000002 271920.16568 1.000000 Const.2 10.048562 2.533762 3.965867 .000073 23122.519745 1.000000 Const.3 8.293774 2.515031 3.297683 .000975 3998.895633 1.000000 Const.4 5.888454 2.488972 2.365818 .017990 360.846977 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  4.70 Standardized regression weights of the latent variable: total -.5444 grp -1.5396 int1.1 1.6712

• END MATRIX -----

  Aitem 4 Matrix

  [DataSet7] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Neuroticism\data.sav

  Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 20.00 6.12 93.88 2.00 89.00 27.22 66.67

  3.00 105.00 32.11 34.56 4.00 97.00 29.66 4.89 5.00 16.00 4.89 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 34.2661 4.5293

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 914.279
• 2 Log-Likelihood of full Model:

  851.295 LR-statistic Chisqu. DF Prob. %-Reduct 62.984 1.000 .000 .069 Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .192213 .025155 7.641271 .000000 1.211929 2.388340 Const.1 -3.531401 .834922 -4.229616 .000023 .029264 1.000000

  Const.2 -5.723395 .842936 -6.789836 .000000 .003269 1.000000 Const.3 -7.266017 .879398 -8.262493 .000000 .000699 1.000000 Const.4 -9.886163 .966175 -10.232273 .000000 .000051 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  18.72 Standardized regression weights of the latent variable: total .4327

• END MATRIX -----

Matrix

  [DataSet7] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Neuroticism\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 20.00 6.12 93.88 2.00 89.00 27.22 66.67

  3.00 105.00 32.11 34.56 4.00 97.00 29.66 4.89

  5.00 16.00 4.89 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 34.2661 4.5293 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ********************

  LR-test that all predictor weights are zero

• 2 Log-Likelihood of Model with Constants only: 914.279
• 2 Log-Likelihood of full Model: 850.678 LR-statistic Chisqu. DF Prob. %-Reduct 63.601 2.000 .000 .070 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .189647 .025350 7.481072 .000000 1.208823 2.360739 grp -.161497 .205530 -.785759 .432009 .850869 .922413 Const.1 -3.198233 .934780 -3.421374 .000623

  .040834 1.000000 Const.2 -5.390381 .941440 -5.725679 .000000 .004560 1.000000

  Const.3 -6.936278 .971998 -7.136102 .000000 .000972 1.000000 Const.4 -9.560424 1.048358 -9.119425 .000000 .000070 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  18.85 Standardized regression weights of the latent variable: total .4266 grp -.0401

• END MATRIX ----- .

Matrix

  [DataSet7] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Neuroticism\data.sav Run MATRIX procedure:

  LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 20.00 6.12 93.88 2.00 89.00 27.22 66.67

  3.00 105.00 32.11 34.56 4.00 97.00 29.66 4.89 5.00 16.00 4.89 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 34.2661 4.5293 grp 1.4740 .5001 int1.1 50.1835 17.5397

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only:

  914.279

• 2 Log-Likelihood of full Model: 843.897 LR-statistic Chisqu. DF Prob. %-Reduct 70.382 3.000 .000 .077 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .012314 .072187 .170589 .864547 1.012390 1.057361 grp -4.297391 1.604019 -2.679140 .007381 .013604 .116592 int1.1 .121834 .046846 2.600743 .009302 1.129566 8.473377

  Const.1 2.913614 2.517597 1.157299 .247150 18.423255 1.000000 Const.2 .671831 2.496617 .269097 .787855 1.957819 1.000000 Const.3 -.884338 2.502470 -.353386 .723799 .412987 1.000000 Const.4 -3.521433 2.519969 -1.397411 .162290 .029557 1.000000 Results assuming a latent continuous variable

  R-Square (%):

  20.06 Standardized regression weights of the latent variable: total .0275 grp -1.0594 int1.1 1.0534

• END MATRIX -----

  Aitem 5

Matrix

  [DataSet11] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Openness\data.sav Run MATRIX procedure:

  LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 7.00 2.14 97.86 2.00 12.00 3.67 94.19

  3.00 129.00 39.45 54.74 4.00 142.00 43.43 11.31 5.00 37.00 11.31 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 47.4924 5.6828

• Estimation Section ********************

  Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 Running Iteration No.:

  5 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 771.259
• 2 Log-Likelihood of full Model:

  608.250 LR-statistic Chisqu. DF Prob. %-Reduct 163.009 1.000 .000 .211 Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .286569 .025477 11.248280 .000000 1.331850 5.096231 Const.1 -8.550714 1.109616 -7.706014 .000000 .000193 1.000000

  Const.2 -9.785768 1.094771 -8.938643 .000000 .000056 1.000000 Const.3 -13.326366 1.206641 -11.044187 .000000 .000002 1.000000 Const.4 -16.467848 1.329688 -12.384742 .000000 .000000 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  44.63 Standardized regression weights of the latent variable: total .6681

• END MATRIX -----

Matrix

  [DataSet11] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Openness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 7.00 2.14 97.86 2.00 12.00 3.67 94.19

  3.00 129.00 39.45 54.74

  4.00 142.00 43.43 11.31 5.00 37.00 11.31 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 47.4924 5.6828 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 Running Iteration No.:

  5

  ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 771.259
• 2 Log-Likelihood of full Model: 608.230 LR-statistic Chisqu. DF Prob. %-Reduct 163.029 2.000 .000 .211 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .286328 .025533 11.213980 .000000 1.331529 5.089244 grp .031480 .224328 .140331 .888398 1.031981 1.015867

  Const.1 -8.585869 1.138017 -7.544591 .000000 .000187 1.000000 Const.2 -9.820864 1.123468 -8.741562 .000000 .000054 1.000000 Const.3 -13.362100 1.233864 -10.829473 .000000 .000002 1.000000 Const.4 -16.503194 1.354028 -12.188225 .000000 .000000 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  44.65 Standardized regression weights of the latent variable: total .6674 grp .0065

• END MATRIX -----

Matrix

  [DataSet11] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Openness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE

  (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 7.00 2.14 97.86 2.00 12.00 3.67 94.19

  3.00 129.00 39.45 54.74 4.00 142.00 43.43 11.31 5.00 37.00 11.31 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 47.4924 5.6828 grp 1.4740 .5001 int1.1 70.3272 26.1332

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 Running Iteration No.:

  5 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 771.259
• 2 Log-Likelihood of full Model: 608.224 LR-statistic Chisqu. DF Prob. %-Reduct 163.035 3.000 .000 .211 Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .281621 .062775 4.486202 .000007 1.325276 4.954924 grp -.125063 1.921665 -.065080 .948110 .882442 .939373 int1.1 .003299 .040216 .082023 .934629 1.003304 1.090029

  Const.1 -8.363047 2.944494 -2.840233 .004508 .000233 1.000000 Const.2 -9.597927 2.940020 -3.264579 .001096 .000068 1.000000 Const.3 -13.139522 2.979458 -4.410038 .000010 .000002 1.000000 Const.4 -16.280838 3.028646 -5.375616 .000000 .000000 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  44.64 Standardized regression weights of the latent variable: total .6565 grp -.0257 int1.1 .0354

• END MATRIX -----

  Aitem 6

Matrix

  [DataSet14] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Extraversion\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 35.00 10.70 89.30 2.00 99.00 30.28 59.02

  3.00 96.00 29.36 29.66 4.00 78.00 23.85 5.81 5.00 19.00 5.81 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 19.7095 2.4403

• Estimation Section ******************** Running Iteration No.:

  1

  Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 960.036
• 2 Log-Likelihood of full Model: 816.993 LR-statistic Chisqu. DF Prob. %-Reduct 143.043 1.000 .000 .149

  Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .566329 .051621 10.970846 .000000 1.761788 3.982984 Const.1 -8.431011 .960647 -8.776393 .000000 .000218 1.000000

  Const.2 -10.617761 1.005429 -10.560433 .000000 .000024 1.000000 Const.3 -12.298961 1.060750 -11.594591 .000000 .000005 1.000000 Const.4 -14.784464 1.163035 -12.711968 .000000 .000000 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  36.73 Standardized regression weights of the latent variable: total .6061

• END MATRIX -----

Matrix

  [DataSet14] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Extraversion\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 35.00 10.70 89.30 2.00 99.00 30.28 59.02

  3.00 96.00 29.36 29.66 4.00 78.00 23.85 5.81 5.00 19.00 5.81 .00 Effective sample size: 327

  Means and standard deviations of independent variables: Mean Std.Dev. total 19.7095 2.4403 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 960.036

• 2 Log-Likelihood of full Model: 805.910 LR-statistic Chisqu. DF Prob. %-Reduct 154.125 2.000 .000 .161 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .590680 .052857 11.175029 .000000 1.805215 4.226837 grp -.695896 .210632 -3.303843 .000954 .498627 .706092 Const.1 -7.853644 .980165 -8.012570 .000000

  .000388 1.000000 Const.2 -10.040083 1.021804 -9.825838 .000000 .000044 1.000000 Const.3 -11.777492 1.076153 -10.944070 .000000 .000008 1.000000 Const.4 -14.345556 1.178219 -12.175632 .000000 .000001 1.000000

  Results assuming a latent continuous variable

• R-Square (%):

  39.17 Standardized regression weights of the latent variable: total .6198 grp -.1496

• END MATRIX -----

Matrix

  [DataSet14] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Extraversion\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 35.00 10.70 89.30 2.00 99.00 30.28 59.02

  3.00 96.00 29.36 29.66 4.00 78.00 23.85 5.81 5.00 19.00 5.81 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 19.7095 2.4403 grp 1.4740 .5001 int1.1 29.1498 10.7509

• Estimation Section ******************** Running Iteration No.:

  1

  Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 960.036
• 2 Log-Likelihood of full Model: 805.888 LR-statistic Chisqu. DF Prob. %-Reduct 154.148 3.000 .000 .161

  Estimations, standard errors, and effects

• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .609085 .134717 4.521214 .000006 1.838748 4.421012 grp -.427542 1.817089 -.235289 .813984 .652110 .807503 int1.1 -.013563 .091225 -.148673 .881812 .986529 .864322

  Const.1 -8.216302 2.630490 -3.123488 .001787 .000270 1.000000 Const.2 -10.402822 2.647082 -3.929921 .000085 .000030 1.000000 Const.3 -12.139953 2.666893 -4.552096 .000005 .000005 1.000000 Const.4 -14.709962 2.721980 -5.404140 .000000 .000000 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  39.16 Standardized regression weights of the latent variable: total .6392 grp -.0919 int1.1 -.0627

• END MATRIX -----

  Aitem 7

Matrix

  [DataSet15] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Agreeableness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 2.00 .61 99.39 2.00 6.00 1.83 97.55

  3.00 96.00 29.36 68.20 4.00 158.00 48.32 19.88 5.00 65.00 19.88 .00

  Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 24.3180 2.6148

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2 Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ********************

  LR-test that all predictor weights are zero

• 2 Log-Likelihood of Model with Constants only: 743.555
• 2 Log-Likelihood of full Model: 621.025 LR-statistic Chisqu. DF Prob. %-Reduct 122.530 1.000 .000 .165 Estimations, standard errors, and effects
• Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .515327 .051831 9.942412 .000000 1.674186 3.847713 Const.1 -6.500286 1.317093 -4.935330 .000001 .001503 1.000000

  Const.2 -7.958116 1.174780 -6.774132 .000000 .000350 1.000000 Const.3 -11.520570 1.234009 -9.335889 .000000 .000010 1.000000 Const.4 -14.360476 1.332177 -10.779705 .000000 .000001 1.000000

  Results assuming a latent continuous variable

• R-Square (%):

  35.56 Standardized regression weights of the latent variable: total .5963

• END MATRIX -----

Matrix

  [DataSet15] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Agreeableness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL)

• Information Section ********************

  Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 2.00 .61 99.39 2.00 6.00 1.83 97.55 3.00 96.00 29.36 68.20 4.00 158.00 48.32 19.88 5.00 65.00 19.88 .00 Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 24.3180 2.6148 grp 1.4740 .5001

• Estimation Section ******************** Running Iteration No.:

  1 Running Iteration No.:

  2

  Running Iteration No.:

  3 Running Iteration No.:

  4 ..... Optimal solution found.

• OUTPUT SECTION ******************** LR-test that all predictor weights are zero
• 2 Log-Likelihood of Model with Constants only: 743.555
• 2 Log-Likelihood of full Model: 620.553 LR-statistic Chisqu. DF Prob. %-Reduct 123.002 2.000 .000 .165 Estimations, standard errors, and effects

  Coeff.=B Std.Err. B/Std.E. Prob. exp(B) exp(B*S) total .510415 .052204 9.777350 .000000 1.665983 3.798608 grp .153173 .222793 .687516 .491758 1.165527 1.079611 Const.1 -6.605116 1.325981 -4.981304 .000001 .001353 1.000000 Const.2 -8.064815 1.185285 -6.804117 .000000 .000314 1.000000 Const.3 -11.628432 1.243988 -9.347707 .000000 .000009 1.000000 Const.4 -14.472286 1.342693 -10.778555 .000000 .000001 1.000000 Results assuming a latent continuous variable

• R-Square (%):

  35.59 Standardized regression weights of the latent variable: total .5905 grp .0339

• END MATRIX -----

  Matrix

  [DataSet15] C:\Users\ASPIRE_7S\Documents\eksp\new\new\revisi\Data krip ktiga\Agreeableness\data.sav Run MATRIX procedure: LOGISTIC REGRESSION with an ORDINAL DEPENDENT VARIBLE (by Steffen M. KUEHNEL) Interaction term total*grp int1.1 total grp

• Information Section ******************** Dependent variable is: item Marginal distribution of dependent variable Value Frequ. Percent %>Value 1.00 2.00 .61 99.39 2.00 6.00 1.83 97.55

  3.00 96.00 29.36 68.20 4.00 158.00 48.32 19.88 5.00 65.00 19.88 .00

  Effective sample size: 327 Means and standard deviations of independent variables: Mean Std.Dev. total 24.3180 2.6148 grp 1.4740 .5001 int1.1 36.0398 13.3438