search for: lmer5

I seem to come to this problem alot, and I can find my way out of it with a loop, but I wish, and wonder if there is a better way. Here's an example (lmer1-5 are a series of lmer objects): bs=data.frame(bic=BIC(lmer1,lmer2,lmer3,lmer4,lmer5)$BIC) rownames(bs)=c('lmer1','lmer2','lmer3','lmer4','lmer5') best=rownames(bs)[bs==min(bs)] > best [1] "lmer5" This tells me that lmer5 is the model with the lowest BIC. I want to start working with lmer5 as the best model, such as fixef(be...

...lright, but they're the same (to any number of decimal places) as I'd get without a weights argument. Just to check that the weights really don't effect it, I tried using only the rows with a weight of 5 (almost 90% of the data) but it was substantially different. Browse[1]> resp.lmer5 <- lmer(SensSSC ~ Block + Season + (1 | Plot) + (1 | Ma) + (1 | Pa) + + (1 | MaPa), subset = SensSSC.N == 5, data = xx) Browse[1]> ran.eff(resp.lmer5) 01 02 03 04 05 06 07 GCAf RankF A 13.435 13.349 13.595 13.914 14.722 13.161 14.414 0.345 2...