Dear all, I am currently analyzing data from a mixed model with lmer. I`ve tried to follow the suggestions for a correct estimation of p-values as discussed at R-Wiki (http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests&s=lme%20and%20aov). mcmcpvalue <- function(samp) {std <- backsolve(chol(var(samp)), cbind(0, t(samp)) - colMeans(samp), transpose = TRUE) sqdist <- colSums(std * std) sum(sqdist[-1] > sqdist[1])/nrow(samp) } Example that works from D. Bates on RWiki: fm1Adg <- lmer(adg ~ InitWt*Treatment - 1 + (1|Block), AvgDailyGain) AdgS1 <- mcmcsamp(fm1Adg, 50000) library(coda) HPDinterval(AdgS1) mcmcpvalue(as.matrix(AdgS1)[, 6:8]) In my example, I must use the HPDinterval of the library(lme4) because of S4 classes I think, and that my Output of HPDinterval is splitted into subsets $fixef, $ST and $sigma. And when I try to extract information exspecially from one subset with @fixef, that gives me not an mcmcpvalue, but the following error message: My example: library(lme4) fm1Marie<-lmer(a ~ covar + b*c + (1|d) + (1|d:e),na.action=na.omit) MarieS1<-mcmcsamp(fm1Marie, 50000) HPDinterval(MarieS1) #gives me an Output with subsets HPDinterval(MarieS1 at fixef) str(MarieS1 at fixef) mcmcpvalue(as.matrix(MarieS1 at fixef)[3:5,]) Error in chol(val(samp)): error in evaluating the argument 'x' in selecting a method for function 'chol'. My questions: Is this because I use a newer version of HPDinterval than D. Bates? Is this because the matrix is not of positive infinites in my case? Can I write an other mcmcpvalue that allows non-positive values in the matrix? How I can even so became mcmcpvalues for my fixed effects? Or can I suppress the slots $ST and $sigma? I`m only interessted in the p-values of my covariable covar and the fixed effects b, c, b:c! Thanks for any advice! Marieantoine PhD. student, Switzerland
However, I have the problem that my model only consists of parameters with just 1 d.f. (intercepts, slopes), so that the "mcmcpvalue" function defined below obviously produces error messages. How can I proceed in estimating the p-values, then? I very much acknowledge any suggestions. Best regards Christoph.
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