I have repeated measures from the same individuals, and I need to account for temporal correlations...my outcome measure is continuous (daily score on a withdrawal scale over three weeks - including 1 week of baseline "smoking as usual" and 2 weeks of abstinence) - and I have been advised that a GEE analysis is appropriate. I see that Genmod does GEE - but I'm not sure if it will take my continuous outcome data - all the examples I can find are for logistic regression type analysis with categorical outcome data....
I can set my dataset up for a repeated measures analysis in Proc Mixed ok - its simply stacked with a column for day - a column for phase (baseline or withdrawal week 1 or 2) - and my outcome variable (withdrawal score). Then you just say:
proc mixed data = data
class subject_id phase
model symptom_score = day phase day*phase
repeated subject = id
But it seems from the examples I can see that proc genmod does not want the data in a stacked format - but instead with each repeated measure (i.e. each day of symptom data in my example) in its own column. However with this format - I don't understand how you specify the outcome variable (i.e. in the example above - there is just 1 column with all the withdrawal scores in it - but now it would be 21 columns if I dont stack my data.....I don't understand how all the day column could have the same name and thus be specified as a single variable for the GEE analysis outcome.
PROC GENMOD uses the same data arrangement as PROC MIXED -- one response variable with multiple observations containing the repeated measurements of each subject. This is illustrated in the examples in the GENMOD documentation: