Dear list members,



I am running a negative binomial glm using glm.nb and would like to model the [zero inflated] counts as a function of Treatment (four different treatments). Samples of counts varied in duration (time searching for animals to count), and the overall population of animals at the sites of the treatments varied. I am interested only in the effect of Treatment but must account for the effects of varying sample durations and varying population sizes.



I have attempted to do this by adding log(Duration) as an offset and 1/PopulationSize as a weight:



glm.nb(Counts ~ Treatment + offset(log(Duration)), weights=1/PopulationSize)



Or should I be adding both of them as offsets?



glm.nb(Counts ~ Treatment + offset(log(Duration)) + offset(log(CD$PodMigHrPeriodWeight)))



I'm confused by the difference in weights and offsets in glm and glm.nb. Any help would be wonderful.



Chandra



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