lmer/pamer.fnc error

Richa Bharti <richabharti74 at ...> writes:

*Dear R group,*

*I am doing lmer with 2 factors and cage and as random effect.*
*
library(lmerTest)
library(LMERConvenienceFunctions)

lmer_null<-lmer(D1 ~ 1 + (1|Cage_Nr), data=data_m)
lmer_full<-lmer(D1 ~ Day*Mutant+Gender+(1|Cage_Nr),
REML=FALSE, data=data_m)
(anova_full<-anova(lmer_null,lmer_full))
summary(lmer_full)
(expl.dev<-pamer.fnc(lmer_full))
but with last command I am getting an error
Error in pf(anova.table[term, "F value"], anova.table[term, "Df"],
nrow(model <at> frame) -  :  

Non-numeric argument to mathematical function

I don't what's the reason of this error? Is my model not
correct or could it any other reason.

It looks like at least this part of LMERConvenienceFunctions must
not have been updated to work with new lme4.
Here's an updated version (I haven't tested carefully,
use at your own risk!)  (The package must not contain any
examples or testing of this function, or this would have failed
a while ago ...)

library(lme4)
library(LMERConvenienceFunctions)
library(lmerTest)
fm1 <- lmer(Reaction~Days+(1|Subject),sleepstudy)
fm2 <- update(fm1,.~.-Days)
print(pamer.fnc(fm1),digits=3)
##      Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F) DenDF(UPPER) Pr(>F,UPPER)
## Days 162703  162703     1   161     169 7.88e-244          178     1.21e-27
##      DenDF(LOWER) Pr(>F,LOWER) expl.dev(%)
## Days          160     7.12e-27       0.286

Transform <- function (`_data`, ..., check.names=TRUE) 
{
    e <- eval(substitute(list(...)), `_data`, parent.frame())
    tags <- names(e)
    inx <- match(tags, names(`_data`))
    matched <- !is.na(inx)
    if (any(matched)) {
        `_data`[inx[matched]] <- e[matched]
        `_data` <- data.frame(`_data`,check.names=check.names)
    }
    if (!all(matched)) 
        do.call("data.frame", c(list(`_data`), e[!matched],
                list(check.names=check.names)))
    else `_data`
}


pamer.fnc <- function (model, ndigits = 4) 
{
    if (length(rownames(anova.table <- anova(model))) == 0) {
        cat("nothing to evaluate: model has only an intercept.\n\n")
        cat("printing model fixed effects:\n")
        fixef(model)
    } else {
        dims <- NULL
        rank.X = qr(getME(model,"X"))$rank
        lower.bound <- sum(sapply(ranef(model),function(x) prod(dim(x))))
        updf <- nobs(model) -  rank.X
        lodf <- updf - lower.bound
        dv <- as.character(formula(model)[[2]])
        ss.tot <- sum(scale(model.frame(model)[[dv]],scale=FALSE)^2)
        aov.table <- as.data.frame(anova(model))
        new.anova.table <-
            Transform(anova.table,
                      `Pr(>F)`=pf(`Mean Sq`,NumDF,DenDF,lower.tail=FALSE),
                      `DenDF(UPPER)` = updf,
                      `Pr(>F,UPPER)`=pf(F.value,NumDF,updf,lower.tail=FALSE),
                      `DenDF(LOWER)` = lodf,
                      `Pr(>F,LOWER)`=pf(F.value,NumDF,lodf,lower.tail=FALSE),
                      `expl.dev(%)`=aov.table[,2]/ss.tot,
                      check.names=FALSE)
        class(new.anova.table) <- class(anova.table)
        return(new.anova.table)
    }
}