Hello R programmers!

I used the package languageR for mixed effect models with the syntax at the end of this posting. I can use pvals.fnc to get p-values for model 1 and 3 (hd_lmer1 and hd_lmer3). Using this with model 2 gives the following error message:

p2 = pvals.fnc(hd_lmer2) Error in pvals.fnc(hd_lmer2) : MCMC sampling is not yet implemented in lme4_0.999375 for models with random correlation parameters

I'd be grateful if any one could help me out on how to get p-values for such models.

Models:

 hd_lmer1 <- lmer(rot~ time + group + sex + gen + (1 | subject) + (1|rot.pre), data = data_long,REML = TRUE)
 hd_lmer2 <- lmer(rot~ time + group + sex + gen + (time | subject) + (1|rot.pre), data = data_long,REML = TRUE)
 hd_lmer3 <- lmer(rot~ time*group + sex + gen + (1 | subject) + (1|rot.pre), data =data_long,REML = TRUE)

rot = time spent by mice on an apparatus; gen= genotype

Yours sincerely,

Babila

 ================================
Julius Tachu Babila 


Max Delbrueck Center for Molecular Medicine
Department of Neuroproteomics
Berlin - Buch



      
	[[alternative HTML version deleted]]


