Longitudinal Proportional Data Modeling

[deleted_user]

am dealing with a problem to model longitudinal proportional data using both GEE (M1) and GLMM (M2). I am not sure if my syntax is correct especially for GEE since most SAS books only cover longitudinal "binary" data. I am even not sure if PROC GENMOD can handle GEE modeling for "repeated proportions". Both proportional and binary data belong to binomial distribution but the former one is in group level while the latter one individual level. Hope any one can share experience or opinion here.

Thanks

Jacob

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M1: GEE
proc genmod data=dsn;
class ID group;
model num/den = time group / link=logit dist=binomial type3;
repeated subject=ID/type=ar(1);
run;

M2: GLMM
proc glimmix data=dsn;
class ID group;
model num/den = time group / link=logit dist=binomial solution;
random int time/subject=ID type=un;
run;

ID time num den rate group
1 1 4 5 0.8 A
1 2 3 4 0.75 A
1 3 3 3 1 A
2 1 6 10 0.6 B
2 2 5 5 1 B
2 3 8 10 0.8 B
3 1 1 2 0.5 A
3 2 2 5 0.4 A
3 3 3 5 0.6 A

Note that rate = num / den