I am looking for advice how to gain and report results using beta regression for an ANCOVA-like model. My model is as follows:
Model <- betareg(plants ~ rain * cows)
The questions I want to answer is whether
cows, or interaction between these two factors have an influence to plant relative biomass (expressed as % in a range of (0;1)). If this was a GLM, I would use
anova(Model) and report results from the likelihood ratio test using
Chisq. Since ANOVA is not suitable for
betareg, I read that I could use
lrtest or wald test and compare it manually, like this:
m1 <- betareg(plants~ 1 ,data = mydata) m2 <- betareg(plants~ cows,data = mydata) m3 <- betareg(plants~ rain ,data = mydata) m4 <- betareg(plants~ rain:cows,data = mydata) lrtest(m1,m2,m3,m4)
However, as I understand this is not correct, as my models are not fully nested (in particular m2 and m3). I am wondering if there is an alternative to compare these models and determine which factors could have significantly affected plant biomass?
P.S. This question is closely related to https://stackoverflow.com/questions/44183329/anova-like-object-for-betaregression however, the answer did not help in my case.