Hello, I have a question regarding the function Betareg. I am a bit new to this package, and maybe I did not understand all the theory behind... My data are proportions (%) of a contaminant (DecaBDE) in blood of birds (n=78) which were GPS-tagged so that we could see what kind of habitat they visited. We are investigating the effects of habitat use on the proportions of that contaminant. The full model is as follow: %contaminant = % time spent in agriculture + % time in urban + % time in St-Lawrence River + having visited a landfill (yes/no).
Coding: Deca.sumBDE <- betareg (DecaJb.sumBDEs ~ Agri.outCol24 + AllLawren.outCol24 + LandfiWstwater.YesNo + UrbanCov1.outCol24, data = mydata). Because I am not yet completely familiar with all the theory underlying beta regressions, I followed one of the examples in the package and created a basic model i.e., no second part specified to model the precision (as you can see from the coding). Somehow all my models produced with betareg (including the intercept only) end up with a negative intercept - but I have no negative data. I was also expecting that the intercept of the null model would be the average of my dependant variable (as in a regular linear regression), but it is not.... Any suggesions ? Could this be happening because I did not fit a two parts model ? Or did I simply misunderstand how to interpret and use beta regressions? Thank you for your time, Marie PhD candidate Canada _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
