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# Specifying EDF option for longitudnal studies in PROC MIANALYZE

Dear All,

I have a quick question, while using SAS proc mianalyze for a longitudinal data with 442 clusters each of size two,what should I specify in the option ( EDF=? ),which  I believe requests the adjusted degrees of freedom be used in the analysis?

proc mianalyze parms(classvar=level)=gmparms edf=?;

Thanks

Tasneem

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Solution
‎06-06-2013 02:21 PM
Posts: 2,655

## Re: Specifying EDF option for longitudnal studies in PROC MIANALYZE

Is there an error degrees of freedom output anywhere in the output you got these estimates from?  I am starting think perhaps not, that everything is tested with a Wald chi-squared, which does not depend on the error degrees of freedom.  Anyway, with an exchangeable error structure for your GEE, you only have 442 subjects, so that is the number I would plug into your formula.  I would use 14 (number of parameters fit plus one [intercept doesn't count], ignoring scale), and obtain edf=424.

However, if I fit this in GLIMMIX, I would specify ddfm=KR2, and then use the value that comes up for denominator degrees of freedom (smallest value) minus 4.

Steve Denham

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Posts: 2,655

## Re: Specifying EDF option for longitudnal studies in PROC MIANALYZE

Hi Tasneem,

The following formula is a good start: edf= Error degrees of freedom expected if dataset were complete, using the proposed model minus Number of values imputed.  You can get the first number by running a side calculation on the first imputation dataset.

Steve Denham

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Posts: 26

## Re: Specifying EDF option for longitudnal studies in PROC MIANALYZE

Hi Steve,

Thank you for your response. As always, it's helpful but just to make sure I understand your formula correctly I was wondering if below is what you meant:

For the longitudinal data with GEE after imputing (at two time points)with total sample size (442*2=884), I have the below model and I imputed ACT, AQLQ, ASES, BMQ thus the

EDF = 442(or884?)-15(# of parameters estimated, should I count "scale"..since this is calculated by default)-4(the # of variables for which I imputed)

Also, a point to note is that in my study there are no missing values at t1 only at time t2 there are missing values..

I would really appreciate any comments and suggestions from you as well as the community.

Thanks

Tasneem

Obs      Imp      Parameter        Estimate          StdErr

1          1          Intercept          0.0229            0.8838

2          1          Gender            -0.3055           0.1828

4          1          Age Group      -0.2936            0.3878

5          1          Age Group       0.5481            0.1816

7          1          SES               -1.0081            0.5467

8          1          SES                0.4542            0.1854

10        1          Smoker            -0.7517           0.8320

12        1          Comorb1         -0.6721            0.2127

14        1          Comorb2         0.0690             0.2645

16        1          ACT                -0.1079            0.0254

17        1          AQLQ             -0.1824            0.0973

18        1          BMQ                0.0226            0.0154

19        1          ASES               0.1280            0.1229

20        1          ACT*ASES       -0.0390            0.0251

21        1          Scale                1.0000            0.0000

Solution
‎06-06-2013 02:21 PM
Posts: 2,655

## Re: Specifying EDF option for longitudnal studies in PROC MIANALYZE

Is there an error degrees of freedom output anywhere in the output you got these estimates from?  I am starting think perhaps not, that everything is tested with a Wald chi-squared, which does not depend on the error degrees of freedom.  Anyway, with an exchangeable error structure for your GEE, you only have 442 subjects, so that is the number I would plug into your formula.  I would use 14 (number of parameters fit plus one [intercept doesn't count], ignoring scale), and obtain edf=424.

However, if I fit this in GLIMMIX, I would specify ddfm=KR2, and then use the value that comes up for denominator degrees of freedom (smallest value) minus 4.

Steve Denham

Contributor
Posts: 26