Thanks for your reply!I successfully fitted another model with the same number of observation (and structure) and the only difference is that cover values were more centered on the mean values.
I just tried to fit the same model by adding a constant cover value to all observations (+0.20) and the model works
I think that the issue derives from very small cover values...
summary(cover_lf$cover) (divided by 100)
Min. 1st Qu. Median Mean 3rd Qu. Max. 0.0000 0.0050 0.0130 0.0252 0.0385 0.1300
Call:glmmadmb(formula = cover ~ time + summit + direction + (1 | plot_id), data = cover_lf, family = "beta")
AIC: -228.7
Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -1.2241 0.0476 -25.72 <2e-16 ***time2015 -0.0688 0.0337 -2.04 0.0410 * summitMAC -0.1407 0.0437 -3.22 0.0013 ** directionN 0.1028 0.0574 1.79 0.0733 . directionS 0.0760 0.0624 1.22 0.2238 directionW 0.0986 0.0574 1.72 0.0860 . ---Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
Number of observations: total=50, plot_id=25 Random effect variance(s):Group=plot_id Variance StdDev(Intercept) 0.003394 0.05826
Beta dispersion parameter: 403.43 (std. err.: 0.00012419)
Log-likelihood: 122.34