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Re: comparing GeneraliZed linear MIXED (GLMM) with GLM REPEATED

Posted by Kornbrot, Diana on Mar 01, 2017; 5:06pm
URL: http://spssx-discussion.165.s1.nabble.com/comparing-GeneraliZed-linear-MIXED-GLMM-with-GLM-REPEATED-tp5733923p5733928.html

Compound symmetry is much less like multivariate than unstructured as it gives very large df for analysis (repeated) and its interactions
Residuals is definitely wrong it gives df as total N -all dos which is MUCH too large.

Here is my problem
I want to recommend a SIMPLE CONSISTENT approach to psychologists that applies to both normal, identify AND binomial, logit analyses.
For normal,  the repeated option is very well known and  used in zillions of studies. As Thom says GLMM unstructured may well be slightly better, and is what I intend recommending.
BUT I would dearly love to understand why I am getting different answers

Another problem  with GLMM is that it often gives up immediately as matrices are problematic - unlike General Estimating Equations, GEE that gives a prompt answer whatever.

GEE is different again and gives chi-square inferential test statistic. 
Again I would dearly love to know why GEE gives chi-square not F
NB GEE also gives too large df2 for repeated predictor

When analyses give too large df2 the p value will be lower thus increasing chance of wrongly rejecting the nuke
All very puzzling - but definitely not going for overlarge df2
thanks for help
best
Diana


On 1 Mar 2017, at 14:46, Bruce Weaver <[hidden email]> wrote:

I was wondering about that too, Gene.  Diana, if that change doesn't get you
all the way there, I'd also try changing DF to RESIDUAL.   



Maguin, Eugene wrote
Isn’t one difference that the genlinmixed model uses an unstructured cov
matrix while the glm model uses the standard repeated measures assumption
of compound symmetry? What happens if you impose a compound symmetry cov
matrix on the genlinmixed model?

Gene Maguin

From: SPSSX(r) Discussion [mailto:

SPSSX-L@.UGA

] On Behalf Of Kornbrot, Diana
Sent: Wednesday, March 01, 2017 4:56 AM
To:

SPSSX-L@.UGA

Subject: comparing GeneraliZed linear MIXED (GLMM) with GLM REPEATED

Hi

One might expect (hope) these procedures would have same results when GLMM
has normal with identity link and some settings.
NOT SO.
Design. this is complex as want to test limits, between factors are very
unbalanced subject variable has n = 87
Factor 1, between: betwennrepeat, 2 level
Factor 2, between: Nlevels, 4 levels
Factor 3, repeated: analysis, 5 levels

Nearest I can get is below with following syntax
GLM repeated
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.

GLMM

*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
Work
University of Hertfordshire
College Lane, Hatfield, Hertfordshire AL10 9AB, UK
+44 (0) 170 728 4626
[hidden email]
http://dianakornbrot.wordpress.com/
 http://go.herts.ac.uk/Diana_Kornbrot
skype:  kornbrotme
Home
19 Elmhurst Avenue
London N2 0LT, UK
 +44 (0) 208 444 2081                                                   



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