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

Posted by Ryan on Mar 03, 2017; 1:03pm
URL: http://spssx-discussion.165.s1.nabble.com/comparing-GeneraliZed-linear-MIXED-GLMM-with-GLM-REPEATED-tp5733923p5733934.html

Diana,

I haven't had time to read your post carefully, but a quick glance at your syntax looks like you employed a mixed (within subjects and between subjects factors) ANOVA. As others mentioned, the tests generated that include the repeated measures factor assume Sphericity from an ANOVA. For a true comparison between a MANOVA and a linear mixed model, you should employ a MANOVA, which assumes an unstructured Sigma matrix. I would also suggest you use the MIXED procedure to start since you are assuming the DVs are conditionally MVN.

What you are trying to accomplish has been done before. The linear mixed modeling procedure in SPSS, and other software for that matter, can accomplish just about everything a general linear modeling procedure can do and more (e.g., better handle unbalanced designs, utilize more restrictive covariance structures).

Ryan

On Wed, Mar 1, 2017 at 4:56 AM, Kornbrot, Diana <[hidden email]> wrote:

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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