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The Art and Science of Test Development—Part F Psychometric/technical statistical analysis:  Internal The basic structure and content of this presentation is grounded extensively on the test development procedures developed by  Dr. Richard Woodcock Kevin S. McGrew, PhD. Educational Psychologist Research Director Woodcock-Muñoz Foundation
“ In god we trust….all others must show data”  (unknown source) Test authors and publishers have  standards-based responsibility  to provide supporting  psychometric technical information re: tests and battery Typically in the form of a series of technical chapters in manual or a separate technical manual
Calculate  psychometric/measurement statistics  for technical manual/chapters ,[object Object]
Calculate summary statistics  (n, means, SDs, SEM) and reliabilities for all tests and clusters by technical age groups etc… etc…
Special reliability analyses  required for  speeded tests Traditional test-retest reliability analysis
Special reliability analyses for all tests More complex  repeated measures reliability analysis (McArdle and Woodcock, 1989—see WJ-R Technical Manual)
Provide evidence based on  internal structure  (internal validity)
Structural (Internal)  Stage of Test Development Purpose Examine the internal relations among the measures used to operationalize the theoretical construct domain (i.e.,  intelligence or cognitive abilities ) Questions asked Do the observed measures “behave” in a manner consistent with the theoretical domain definition of intelligence? Method and concepts ,[object Object],[object Object],[object Object],Characteristics of strong test validity program ,[object Object],[object Object],[object Object]
etc… Structural/internal validity evidence :  Test and cluster inter-correlation matrices  by technical age groups etc…
Structural/internal validity Confirmatory factor analysis  by  major age groups ( exploratory factor analysis  if  not  theory-driven test blueprint)
Structural/internal validit y  Confirmatory factor analysis  by  major age groups ( exploratory factor analysis  if  not  theory-driven test blueprint) .67 .53 .40 .42 .43
 
Structural (Internal)  Stage of Test Development Purpose Examine the internal relations among the measures used to operationalize the theoretical construct domain (i.e.,  intelligence or cognitive abilities ) Questions asked Do the observed measures “behave” in a manner consistent with the theoretical domain definition of intelligence? Method and concepts ,[object Object],Characteristics of strong test validity program ,[object Object]
The WJ III factor structure model  provided the best fit  to the data when compared to  six alternative models The conclusion was the same across 5 age-differentiated samples  Structural/internal validity:  Confirmatory factor analysis model comparisons  by major age groups
Internal validity evidence example:  g-loadings  for differentially weighted  General Intellectual Ability  cluster
Provide evidence based on  internal structure:  Developmental evidence?
Developmental evidence  in the form of  differential  growth curves of measures
Provide  Test Fairness  Evidence
= White Non-White Structural/internal validity Evaluating structural invariance with Multiple Group CFA
= Male Female Structural/internal validity Evaluating structural invariance with Multiple Group CFA
= Hispanic Non-Hispanic Structural/internal validity Evaluating structural invariance with Multiple Group CFA
Test fairness evidence:  Item Level Analyses:  Differential Item Functioning (DIF) ,[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],Test fairness evidence:  Item Level Analyses:  Differential Item Functioning (DIF)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],(cont. next slide)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
End of Part F  Additional steps in test development process will be presented in subsequent modules as they are developed

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Applied Psych Test Design Part F: Psychometric/technical statistical analysis: Internal

  • 1. The Art and Science of Test Development—Part F Psychometric/technical statistical analysis: Internal The basic structure and content of this presentation is grounded extensively on the test development procedures developed by Dr. Richard Woodcock Kevin S. McGrew, PhD. Educational Psychologist Research Director Woodcock-Muñoz Foundation
  • 2. “ In god we trust….all others must show data” (unknown source) Test authors and publishers have standards-based responsibility to provide supporting psychometric technical information re: tests and battery Typically in the form of a series of technical chapters in manual or a separate technical manual
  • 3.
  • 4. Calculate summary statistics (n, means, SDs, SEM) and reliabilities for all tests and clusters by technical age groups etc… etc…
  • 5. Special reliability analyses required for speeded tests Traditional test-retest reliability analysis
  • 6. Special reliability analyses for all tests More complex repeated measures reliability analysis (McArdle and Woodcock, 1989—see WJ-R Technical Manual)
  • 7. Provide evidence based on internal structure (internal validity)
  • 8.
  • 9. etc… Structural/internal validity evidence : Test and cluster inter-correlation matrices by technical age groups etc…
  • 10. Structural/internal validity Confirmatory factor analysis by major age groups ( exploratory factor analysis if not theory-driven test blueprint)
  • 11. Structural/internal validit y Confirmatory factor analysis by major age groups ( exploratory factor analysis if not theory-driven test blueprint) .67 .53 .40 .42 .43
  • 12.  
  • 13.
  • 14. The WJ III factor structure model provided the best fit to the data when compared to six alternative models The conclusion was the same across 5 age-differentiated samples Structural/internal validity: Confirmatory factor analysis model comparisons by major age groups
  • 15. Internal validity evidence example: g-loadings for differentially weighted General Intellectual Ability cluster
  • 16. Provide evidence based on internal structure: Developmental evidence?
  • 17. Developmental evidence in the form of differential growth curves of measures
  • 18. Provide Test Fairness Evidence
  • 19. = White Non-White Structural/internal validity Evaluating structural invariance with Multiple Group CFA
  • 20. = Male Female Structural/internal validity Evaluating structural invariance with Multiple Group CFA
  • 21. = Hispanic Non-Hispanic Structural/internal validity Evaluating structural invariance with Multiple Group CFA
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27. End of Part F Additional steps in test development process will be presented in subsequent modules as they are developed

Editor's Notes

  1. d
  2. NOTE: Reliability statistics calculated for all WJ III tests across their range of intended use. Included all norming subjects tested at each technical age level. (25 levels - by year 2-19, by 10 yr.intervals 20-79, 80+) Split-half coefficients corrected for length using Spearman-Brown correction Rasch analysis procedures used for calculating reliability for 8 multi-point tests (4 in COG, 4 in ACH) and 8 speeded (5 in COG, 3 in ACH) Test-retest study also conducted for 8 speeded tests Interval set at 1 day to minimize changes in test scores due to changes in the subjects’ states or traits. These reliabilities are lower than those for same tests obtained using Rasch analysis procedures. Test-retest is lower bound for speeded tests - other reliabilities are upper bound. TESTS: 38 of 42 are .80 or higher (15 are .90 or higher) (4 are in .70s) CLUSTERS: 36 of 42 are .90 or higher (6 are in .80s) Consult: Chapter 3 of Technical Manual for more information. Summary information in ASB 2.