http://spssx-discussion.165.s1.nabble.com/Get-Pairwise-Comparison-in-GEE-Ordinal-logistic-model-tp5736468p5736495.html
As an aside, I have concerns about the “ItemNo*Repetition*InputMode” within-subject and “independent” covariance structure specifications.
> On Aug 14, 2018, at 2:43 PM, Bruce Weaver <
[hidden email]> wrote:
>
> Normally, I would use EMMEANS with COMPARE to get pairwise contrasts. But as
> the FM says regarding this particular model:
>
> "Estimated marginal means are not available if the multinomial distribution
> is used. If DISTRIBUTION = MULTINOMIAL on the MODEL subcommand and the
> EMMEANS subcommand is specified, then EMMEANS is ignored and a warning is
> issued."
>
> I don't immediately see another straightforward approach.
>
> One can get GENLIN to spit out a vector of regression coefficients and a
> covariance matrix for the parameters. So with some application of matrix
> algebra, one should be able to make whatever comparisons they wish. Several
> years ago, I wrote a macro to do that (when the boss was asking awkward
> questions). It works well for ordinary (binary) logistic regression, but I
> never considered whether it would work with a multinomial outcome variable.
> I would not be surprised if it needed some tweaking. You can find that
> macro (!MLEcomp) with an example here:
>
>
>
https://sites.google.com/a/lakeheadu.ca/bweaver/Home/statistics/spss/olscomp_mlecomp>
> If this is a one-time job and elegance is not high on the priority list,
> another clunky but less complicated way might be to estimate the model
> multiple times, changing the reference category for the variable(s) of
> interest each time. By doing this, I think you should be able to get all of
> the comparisons of interest. (If I was going to try this, I'd use OMS to
> write the parameter estimates out to another data set.)
>
> But with any luck, someone else will come through with a much simpler
> approach.
>
> HTH.
>
>
>
> sara2016 wrote
>> Here is the Syntax
>>
>> DATASET ACTIVATE DataSet1.
>> * Generalized Estimating Equations.
>> GENLIN FamilarityScore (ORDER=ASCENDING) BY Repetition InputMode
>> (ORDER=ASCENDING) WITH
>> ProficiencyLevel
>> /MODEL Repetition InputMode ProficiencyLevel Repetition*InputMode
>> DISTRIBUTION=MULTINOMIAL LINK=CUMLOGIT
>> /CRITERIA METHOD=FISHER(1) SCALE=1 MAXITERATIONS=100 MAXSTEPHALVING=5
>> PCONVERGE=1E-006(ABSOLUTE)
>> SINGULAR=1E-012 ANALYSISTYPE=3(WALD) CILEVEL=95 LIKELIHOOD=FULL
>> /REPEATED SUBJECT=Participant WITHINSUBJECT=ItemNo*Repetition*InputMode
>> SORT=YES
>> CORRTYPE=INDEPENDENT ADJUSTCORR=YES COVB=ROBUST MAXITERATIONS=100
>> PCONVERGE=1e-006(ABSOLUTE)
>> UPDATECORR=1
>> /MISSING CLASSMISSING=EXCLUDE
>> /PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION (EXPONENTIATED).
>>
>>
>> Thank you.
>>
>>
>>
>>
>>
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>
>
> -----
> --
> Bruce Weaver
>
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>
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