You are correct that the multivariate omnibus tests are in fact multivariate, but those are followed by univariate tests in the output. There is much more flexibility using the MANOVA command.
Ryan
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repeated does NOT assume sphericity fro multivariate tests - it uses unstructured covariance and makes various assumption about df2. it does assume normality
further investigation suggests that REPEATED with Roy’s largest root is very close to mixed, generalised linear, with normal and identity covariance unstructured, build Sattertthwaite df, with model covariance matrix
here mixed gives df2 = N - number of estimated parameters from main and between factors for all comparisonswhile repeated also subtracts the df appropriate to the relevant within comparison
not a lot of people know that!
in fact, the number of ways of choking the options is rather more than the number of contributors to the debatebestDiana
On 3 Mar 2017, at 13:03, Ryan Black <[hidden email]> wrote:
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).
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On Wed, Mar 1, 2017 at 4:56 AM, Kornbrot, Diana <[hidden email]> wrote:
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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 = 87Factor 1, between: betwennrepeat, 2 levelFactor 2, between: Nlevels, 4 levelsFactor 3, repeated: analysis, 5 levels
Nearest I can get is below with following syntaxGLM repeatedGLM 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 boldGENLINMIXED/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 GLMMNote on dfFor between factors there are 7 =(4-1 for Nlevels) + (2-1 for bewennrepeat) +1 for grand meanFor GGLMM: df2 = 80 for all F testsFor repeated Roy’s: between factors still have df2 = 80Repeated factors have lower df,as the related measures df are also taken into accountComparison
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 factorWHY?, WHICH RESULTS are to be recommended?bestDiana
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Professor Diana Kornbrot
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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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