http://spssx-discussion.165.s1.nabble.com/comparing-GeneraliZed-linear-MIXED-GLMM-with-GLM-REPEATED-tp5733923.html
One might expect (hope) these procedures would have same results when GLMM has normal with identity link and some settings.
GLM raw_f lgt_f z_f FlogitVC_f FprobitVC_f BY bewennrepeat Nlevels
/WSFACTOR=analysis 5 Repeated
/CONTRAST(Nlevels)=Repeated
/METHOD=SSTYPE(3)
/EMMEANS=TABLES(OVERALL)
/EMMEANS=TABLES(bewennrepeat)
/EMMEANS=TABLES(Nlevels)
/EMMEANS=TABLES(analysis)
/EMMEANS=TABLES(bewennrepeat*Nlevels)
/EMMEANS=TABLES(bewennrepeat*analysis)
/EMMEANS=TABLES(Nlevels*analysis)
/EMMEANS=TABLES(bewennrepeat*Nlevels*analysis)
/PRINT=DESCRIPTIVE ETASQ HOMOGENEITY
/CRITERIA=ALPHA(.05)
/WSDESIGN=analysis
/DESIGN=bewennrepeat Nlevels bewennrepeat*Nlevels.
*Generalized Linear Mixed Models.Key settings in bold
GENLINMIXED
/DATA_STRUCTURE SUBJECTS=id REPEATED_MEASURES=analysis COVARIANCE_TYPE=UNSTRUCTURED
/FIELDS TARGET=trans1 TRIALS=NONE OFFSET=NONE
/TARGET_OPTIONS DISTRIBUTION=NORMAL LINK=IDENTITY
/FIXED EFFECTS=analysis bewennrepeat Nlevels analysis*bewennrepeat analysis*Nlevels bewennrepeat*Nlevels analysis*bewennrepeat*Nlevels USE_INTERCEPT=TRUE
/BUILD_OPTIONS TARGET_CATEGORY_ORDER=ASCENDING INPUTS_CATEGORY_ORDER=ASCENDING MAX_ITERATIONS=100 CONFIDENCE_LEVEL=95 DF_METHOD=SATTERTHWAITE COVB=MODEL PCONVERGE=0.000001(ABSOLUTE) SCORING=0 SINGULAR=0.000000000001
/EMMEANS TABLES=analysis COMPARE=analysis CONTRAST=PAIRWISE
/EMMEANS TABLES=bewennrepeat CONTRAST=NONE
/EMMEANS TABLES=Nlevels COMPARE=Nlevels CONTRAST=PAIRWISE
/EMMEANS TABLES=analysis*bewennrepeat COMPARE=analysis CONTRAST=PAIRWISE
/EMMEANS TABLES=analysis*Nlevels COMPARE=analysis CONTRAST=PAIRWISE
/EMMEANS TABLES=bewennrepeat*Nlevels COMPARE=bewennrepeat CONTRAST=PAIRWISE
/EMMEANS TABLES=analysis*bewennrepeat*Nlevels COMPARE=analysis CONTRAST=PAIRWISE
/EMMEANS_OPTIONS SCALE=ORIGINAL PADJUST=LSD.
Results.
For GLM repeated have only included Roy’s largest root,as this is nearest to GLMM
Note on df
For between factors there are 7 =(4-1 for Nlevels) + (2-1 for bewennrepeat) +1 for grand mean
For GGLMM: df2 = 80 for all F tests
For repeated Roy’s: between factors still have df2 = 80
Repeated factors have lower df,as the related measures df are also taken into account
Comparison
| GLMM unnstructured |
satterthwaite |
model |
|
|
Multivariate Tests |
Roy's largest root |
|
| Source |
F |
df1 |
df2 |
Sig. |
Effect |
F |
df1 |
Error df |
Sig. |
| analysis |
6.52 |
4 |
80 |
.000136 |
analysis |
6.27 |
4 |
77 |
.000201 |
| bewennrepeat |
21.04 |
1 |
80 |
.000016 |
bewennrepeat |
21.04 |
1 |
80 |
.000016 |
| Nlevels |
.10 |
3 |
80 |
.962591 |
Nlevels |
.10 |
3 |
80 |
.962591 |
| analysis * bewennrepeat |
7.79 |
4 |
80 |
.000024 |
analysis * bewennrepeat |
7.49 |
4 |
77 |
.000038 |
| analysis * Nlevels |
.76 |
12 |
80 |
.688855 |
analysis * Nlevels |
1.76 |
4 |
79 |
.145261 |
| bewennrepeat * Nlevels |
.25 |
2 |
80 |
.783290 |
bewennrepeat * Nlevels |
.25 |
3 |
80 |
.864661 |
The results are identical for between factors,
BUT slightly different for repeated factor
WHY?, WHICH RESULTS are to be recommended?
best
Diana
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Professor Diana Kornbrot
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