1 / 22

DIF

DIF. Winsteps: MFQ & DIF. Sample. 2500 “boys” and 2500 “girls” All roughly 14 years old Data collected from ALSPAC hands-on clinic Short-form (13-item) MFQ. odd / even items. [01] I felt miserable or unhappy [02] I didn't enjoy anything at all

jirair
Download Presentation

DIF

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. DIF

  2. Winsteps: MFQ & DIF

  3. Sample • 2500 “boys” and 2500 “girls” • All roughly 14 years old • Data collected from ALSPAC hands-on clinic • Short-form (13-item) MFQ

  4. odd / even items • [01] I felt miserable or unhappy • [02] I didn't enjoy anything at all • [03] I felt so tired I just sat around and did nothing • [04] I was very restless • [05] I felt I was no good any more • [06] I cried a lot • [07] I found it hard to think properly or concentrate • [08] I hated myself • [09] I was a bad person • [10] I felt lonely • [11] I thought nobody really loved me • [12] I thought I could never been as good as other kids • [13] I did everything wrong

  5. Assessment of non-uniform gender DIF using PCM in Winsteps

  6. Non-uniform DIF plots

  7. Case 1 Item fits model well

  8. Case 2 • Item fits model poorly • PCM (Rasch) model • assumes equal slopes • for all items – • but performance of • item similar across • genders

  9. Case 3 Item fits model well at population level but evidence of different functioning across genders For a given trait level, boys are less likely to endorse the item (crying) than girls are ICCs appear to diverge

  10. Case 4 Item fits model well at population level but evidence of different functioning across genders For a given trait level, boys are more likely to endorse the item (being as good as other kids) than girls are ICCs appear parallel

  11. Assessment of gender DIF using GRM MIMIC model in Mplus

  12. Simple unidimensional trait model i1 i3 i6 i8 i10 i12 F

  13. Effect of gender on trait i1 i3 i6 i8 i10 i12 F Gender

  14. Model for gender main-effect on trait Data: File is "C:\work\courses\summer_school\MFQ\mplus\mfq_14yr_5000.dta.dat" ; Variable: Names are sex ID ta01_012 ta02_012 ta03_012 ta04_012 ta05_012 ta06_012 ta07_012 ta08_012 ta09_012 ta10_012 ta11_012 ta12_012 ta13_012 ta01_001 ta01_011 ta02_001 ta02_011 ta03_001 ta03_011 ta04_001 ta04_011 ta05_001 ta05_011 ta06_001 ta06_011 ta07_001 ta07_011 ta08_001 ta08_011 ta09_001 ta09_011 ta10_001 ta10_011 ta11_001 ta11_011 ta12_001 ta12_011 ta13_001 ta13_011; Missing are all (-9999) ; usevariables = ta01_012 ta03_012 ta06_012 ta08_012 ta10_012 ta12_012 sex; categorical = ta01_012 ta03_012 ta06_012 ta08_012 ta10_012 ta12_012; Analysis: estimator = MLR ; link = probit; model: F by ta01_012* ta03_012 ta06_012 ta08_012 ta10_012 ta12_012; F@1; F on sex;

  15. Estimate S.E. Est./S.E. P-Value F BY TA01_012 1.284 0.058 22.017 0.000 TA03_012 0.556 0.029 19.162 0.000 TA06_012 1.176 0.066 17.863 0.000 TA08_012 1.851 0.159 11.679 0.000 TA10_012 1.264 0.064 19.696 0.000 TA12_012 1.119 0.064 17.375 0.000 F ON SEX 0.260 0.036 7.146 0.000 Thresholds TA01_012$1 0.859 0.084 10.251 0.000 TA01_012$2 3.326 0.130 25.528 0.000 TA03_012$1 0.934 0.042 22.414 0.000 TA03_012$2 2.493 0.061 41.130 0.000 TA06_012$1 2.671 0.123 21.697 0.000 TA06_012$2 4.372 0.175 25.009 0.000 TA08_012$1 3.925 0.280 14.017 0.000 TA08_012$2 6.158 0.414 14.863 0.000 TA10_012$1 2.151 0.106 20.379 0.000 TA10_012$2 4.284 0.158 27.168 0.000 TA12_012$1 2.116 0.096 21.993 0.000 TA12_012$2 3.676 0.134 27.519 0.000 Residual Variances F 1.000 0.000 999.000 999.000

  16. Uniform DIFDirect effect of gender on item i1 i3 i6 i8 i10 i12 F Gender

  17. Model for uniform DIF model: F by ta01_012* ta03_012 ta06_012 ta08_012 ta10_012 ta12_012; F@1; F on sex; ! ta01_012 on sex; ! ta03_012 on sex; ta06_012 on sex; ! ta08_012 on sex; ! ta10_012 on sex; ! ta12_012 on sex;

  18. Estimate S.E. Est./S.E. P-Value F BY TA01_012 1.283 0.058 22.007 0.000 TA03_012 0.556 0.029 19.150 0.000 TA06_012 1.165 0.066 17.646 0.000 TA08_012 1.872 0.162 11.587 0.000 TA10_012 1.265 0.064 19.791 0.000 TA12_012 1.134 0.065 17.364 0.000 F ON SEX 0.233 0.037 6.374 0.000 TA06_012 ON SEX 0.365 0.073 5.005 0.000 Thresholds TA01_012$1 0.808 0.084 9.618 0.000 TA01_012$2 3.272 0.130 25.203 0.000 TA03_012$1 0.912 0.042 21.960 0.000 TA03_012$2 2.471 0.060 40.973 0.000 TA06_012$1 3.191 0.164 19.495 0.000 TA06_012$2 4.910 0.205 23.977 0.000 TA08_012$1 3.884 0.282 13.766 0.000 TA08_012$2 6.136 0.419 14.634 0.000 TA10_012$1 2.100 0.104 20.115 0.000 TA10_012$2 4.229 0.156 27.148 0.000 TA12_012$1 2.087 0.097 21.581 0.000 TA12_012$2 3.658 0.135 27.182 0.000 Residual Variances F 1.000 0.000 999.000 999.000

  19. 6 DIFferent models Two-Tailed Estimate S.E. Est./S.E. P-Value TA01_012 ON SEX 0.095 0.052 1.801 0.072 TA03_012 ON SEX 0.038 0.041 0.917 0.359 TA06_012 ON SEX 0.365 0.073 5.005 0.000 TA08_012 ON SEX -0.161 0.099 -1.635 0.102 TA10_012 ON SEX 0.019 0.060 0.308 0.758 TA12_012 ON SEX -0.362 0.062 -5.887 0.000

  20. Uniform gender-DIF for item 6 Male ICC’s are shifted to the right For a given trait level (depressive symptoms) boys are less likely than girls to endorse crying item

  21. Uniform gender-DIF for item 12 Female ICC’s are shifted to the right For a given trait level (depressive symptoms) boys are more likely than girls to endorse the item ‘being as good as other kids’

  22. Non-uniform DIFInteraction effect of gender*F on item i1 i3 i6 i8 i10 i12 F Gender Model must be fitted in a multiple group set up constraining parameters across (gender) groups

More Related