I am using lmer to describe patterns in stream variables between
streams draining watersheds with different land uses. I need to make
some kind of determination of significance. I understand that mixed
models cannot provide accurate p values because the denominator df is
unknown. As per D. Bates recommendation in his post "lmer, p-values
and all that" I used mcmcsamp and HPDinterval to get 95% "confidence
intervals." These intervals were very large and suggest that there are
no significant differences in variables where differences seem
obvious. I'll use one of my variables as an example: total stream
nitrogen. There are 12 streams and 24 sites (two riparian types per
stream).
model<-lmer(TN ~ wsh*rip + (1|stream), data=all24)
Data: all24
AIC BIC logLik deviance REMLdev
78.47 90.25 -29.24 65.15 58.47
Random effects:
Groups Name Variance Std.Dev.
stream (Intercept) 4.10443 2.0259
Residual 0.20885 0.4570
Number of obs: 24, groups: stream, 12