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
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•
•
•
Calculate Estimates
View the output path diagram
Standardized
View Text (Output)
Text Output
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•
•
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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
CODING
.000
OBJECT
.159
.000
BLOCK
.758
.156
.000
PARANG
.049
-.180
.358
.000
-1.513
.331
-.301
-.414
.000
2.062
-1.248
-1.098
.519
-.805
.000
.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
-.333
-.872
-.965
-.127
-.464
.618
PICTCOMP
DIGIT
VOCAB
INFO
Large residuals for Comp-Pictcomp
and Digit-Coding.
Fit
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•
•
•
GFI = .931
CFI = .941
RMSEA = .06
Fit is not bad.
Modification Indices
M.I.
4.509
5.513
4.194
4.608
4.065
4.276
Par Change
.171
-.194
-.138
.143
-.122
-.109
CODING
OBJECT
PICTCOMP
DIGIT
VOCAB
ARITH
<--<--<--<--<--<---
DIGIT
ARITH
CODING
CODING
PARANG
OBJECT
COMP
<---
Performance
IQ
4.569
.438
COMP
COMP
<--<---
OBJECT
PICTCOMP
5.317
7.109
.142
.159
I am going to add a path from Performance to
COMP.
CFA-Wisc2.amw
has this path
diagram.
2 Dropped Significantly
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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
COMP
INFO
PICTCOMP
VOCAB
SIMIL
ARITH
CODING
OBJECT
BLOCK
PARANG
<--<--<--<--<--<--<--<--<--<---
Verbal IQ
Verbal IQ
Performance IQ
Verbal IQ
Verbal IQ
Verbal IQ
Performance IQ
Performance IQ
Performance IQ
Performance IQ
Estimat
e
1.491
2.256
1.790
2.273
2.205
1.307
.200
1.633
1.823
1.189
S.E.
C.R.
P
.254
.200
.239
.201
.227
.173
.253
.234
.219
.224
5.860
11.286
7.474
11.297
9.721
7.562
.791
6.990
8.310
5.302
***
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***
***
***
***
.429
***
***
***
• The path to CODING is not significant. I
am going to eliminate CODING.
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