Thank you for your commentaries and suggestions. Site 0 and site 1 are interpretable like events. In fact these data come from a simultaneous observations of individuals in two different sites (so they are independent observations: while one individual is observed in one site it can't be in another).
Each individual is assigned to age "0" (first year of age), or "1" (all the rest); even though it may seem a very strong (brutal?) pooling, from a biological point of view it makes sense given these two classes of individuals are quite homogeneous in their dispersal behavior within each age class (0 or 1). The goal of this analysis is just to characterize their dispersal behavior (which individuals stay home at site 0 and which ones disperse to site 1? About the "birth" issue, here I am more in doubt. "Birth" relates to the month of birth (5= May, 6= June, 7= July). It seems to me too it is a quite severe pooling (one individual born 1st June is 5 as one individual born 30th June but one individual born 30th May or 1st July is 4 or 6 - it doesn't make much sense). Anyway I didn't find a way to better measure this variable as there is no a real starting and ending point, more or less individuals may born since 1st May up to 31th July (I mean in my data set there are no individuals born before and after these dates). Any hint? -- View this message in context: http://r.789695.n4.nabble.com/Chi-square-value-of-anova-binomialglmnull-binomglmmod-test-Chisq-tp4632293p4632380.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
