Confirmatory Factor Analysis SPSS/AMOS

The WISC, Verbal IQ INFOrmation – general knowledge questions COMPrehension – of social situations and common concepts ARITHmetic SIMILarities – how are two words similar VOCABulary DIGITspan – repeating strings of digits after hearing them

The WISC, Performance IQ PICTureCOMPletion – identify the missing part PictureARrANGement – arrange pictures to tell a story. BLOCK design – arrange blocks to match model. OBJECT assembly – puzzles involvement arrangement into a whole CODING – associate simple shapes with symbols coding them

Download From BlackBoard CFA-WISC.sav CFA-Wisc.amw CFA-Wisc2.amw CFA-Wisc-Amos-Output.doc Bring CFA-WISC into SPSS Analyze, AMOS

AMOS Open, CFA-Wisc.amw Select Data Files, Working, View Data, OK Analysis Properties Minimization history Standardized estimates Squared multiple correlations Residual moments Modification indices

Calculate Estimates View the output path diagram Standardized View Text (Output)

Text Output Chi-square = 70.236 Degrees of freedom = 43 Probability level = .005 Poor fit or just too much power?

Standardized Residual Covariances   CODING OBJECT BLOCK PARANG PICTCOMP DIGIT .000 .159 .758 .156 .049 -.180 .358 -1.513 .331 -.301 -.414 2.062 -1.248 -1.098 .519 -.805 VOCAB .886 -.908 -.152 -1.058 .199 -.079 SIMIL -.931 .443 -.272 1.327 1.573 -.191 ARITH .872 -1.884 .576 .905 -.553 .623 COMP .413 1.186 1.159 -.073 2.112 -.431 INFO -.333 -.872 -.965 -.127 -.464 .618 Large residuals for Comp-Pictcomp and Digit-Coding.

Fit GFI = .931 CFI = .941 RMSEA = .06 Fit is not bad.

Modification Indices   M.I. Par Change CODING <--- DIGIT 4.509 .171 OBJECT ARITH 5.513 -.194 PICTCOMP 4.194 -.138 4.608 .143 VOCAB PARANG 4.065 -.122 4.276 -.109 COMP Performance IQ 4.569 .438 5.317 .142 7.109 .159 I am going to add a path from Performance to COMP.

CFA-Wisc2.amw has this path diagram.

2 Dropped Significantly Chi-square = 60.295 Degrees of freedom = 42 Probability level = .033 Change in 2 = (70.326 – 20.295) = 9.94 On 1 df, is significant.

Better Fit GFI = .942, had been .931 CFI = .960, had been .941 RMSEA = .050, had been .060

Regression Weights The path to CODING is not significant. I am going to eliminate CODING.   Estimate S.E. C.R. P COMP <--- Verbal IQ 1.491 .254 5.860 *** INFO 2.256 .200 11.286 PICTCOMP Performance IQ 1.790 .239 7.474 VOCAB 2.273 .201 11.297 SIMIL 2.205 .227 9.721 ARITH 1.307 .173 7.562 CODING .253 .791 .429 OBJECT 1.633 .234 6.990 BLOCK 1.823 .219 8.310 PARANG 1.189 .224 5.302

CFA-Wisc3.amw has this path diagram.

2 No Longer Significant Chi-square = 45.018 Degrees of freedom = 33 Probability level = .079

Yet Better Fit GFI = .952, had been .942 CFI = .974, had been .960 RMSEA = .046, had been .050