I am conducting an analysis of the effect of sex on number of dispersal events in a rodent. Basically, we're interested in seeing whether males or females travel more between communities. There are repeated measures because individuals were followed on multiple nights, and the dependent variable is the number of visits per night. It's unclear to me whether I need to worry about overdispersion with the repeated measures model. I understand that the typical ways of testing for overdispersion (goodness of fit tests with deviance or pearson stats) aren't appropriate, and it seems that using a repeated measures analysis is typically considered a way of combatting overdispersion. So should I just not worry about it? Code is below... proc genmod data = nvissex; class ssex sname; model nvis = ssex/dist=poisson link=log type3; repeated subject = sname/type=ar(1) corrw; lsmeans ssex/diff cl; run; Key: nvis = visits per night ssex = sex (male or female) sname = individual ID
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