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Confidence Interval of random effect variances in lmer
2 messages · tommy gaillard, Ben Bolker
tommy gaillard <tommy.gaillard40 at ...> writes:
Hi all,
I have sent a similar post lately but this one is updated.
I would like to obtain the Confidence Interval of random effect * variances*
(intercept and slope) in a lmer model . Here is the model to make this
clear:
fit<-lmer(logitprop_vig~logdensity+logbiomasstrue+
loggpsize+position+(1+logdensity|Idtag),na.action=na.omit,
data=tabimpala)
I am interested in the following output
Random effects:
Groups Name Variance Std.Dev. Corr
Idtag (Intercept) 0.000000 0.00000
logdensity 0.050391 0.22448 NaN
Residual 1.552516 1.24600
Number of obs: 283, groups: Idtag, 15
I need to obtain the CI of the variance of the intercept and slope of the
variable "logdensity".
In principle you should be able to get confidence intervals with the development version of lme4: see the installation notes at the *bottom* of https://github.com/lme4/lme4/ , e.g. library(lme4) fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy) pp <- profile(fm1) confint(pp) However, you are quite likely to have difficulty with this because one of your random effects is estimated as zero. You might try MCMCglmm: library(MCMCglmm) mm <- MCMCglmm(Reaction ~ Days, random = ~us(Days):Subject, data=sleepstudy) summary(mm) the 'G-structure' part of the output gives you lower and upper bounds on the 95% credible interval.
I have tried different packages and functions but it is failing to work. The one I believe that could work is the profile () function from the lm4a package but I did not manage to get this latter in R. If someone knows how to make this work , I would be glad to hear it! I believe this is very important in different field to obtain those values as it would allow to knwo the magnitude of the variabilty estimates and their uncertainty. Any help would be very appreciated. Thank you