I realized I need to use the package survey to be able to include sample weights in my regression analysis. Initially, I wanted to use a negative binomial regression on each one of my outcomes as count data is more often than not overdispersed, so I tried using svyglm.nb. However, for one of the outcomes which has small values, svyglm.nb makes my program crash, so I think there might be some convergence issue. I thought using a Poisson regression might solve the problem, but I would like to be able to test for overdispersion before doing this. There are plenty of functions that test for overdispersion for glm objects, but I was wondering if there were any way to test this hypothesis when the object is of class svyglm and to determine if it is okay to indeed use a Poisson regression?
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I think you'll find your answers here: https://stats.stackexchange.com/questions/66586/is-there-a-test-to-determine-whether-glm-overdispersion-is-significant – slamballais Jun 08 '21 at 20:35
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It seems to work, thank you very much! – airpoll_epi Jun 10 '21 at 04:23