On 14-07-13 01:37 PM, Nick Lange wrote:
Thanks, Ben, Yes, a warning not and error, thanks. And also, yes, this is the first time I've used gamm4. I tried coef(summary(fit$mer)) and it gave an improved regression summary table, but without p-values: Estimate Std. Error t value X(Intercept) 1310.68401 9.204793 142.3914670 Xs(AgeYears)Fx1 19.89873 25.072824 0.7936372 which I can't calculate without the df (but it's large).
I'm not surprised that you don't get p-values: there is even an R FAQ on this subject http://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-are-p_002dvalues-not-displayed-when-using-lmer_0028_0029_003f (which simply refers to https://stat.ethz.ch/pipermail/r-help/2006-May/094765.html -- you may also want to look at http://glmm.wikidot.com/faq)
My colleague has the same versions as I do, except she's running lme4 1.1-6 not lme4 1.1-7. Everything works fine for her.
I'm not surprised she doesn't get the warning messages (those were introduced in 1.1-6), but I *am* surprised if she gets p-values. Since you have large degrees of freedom, you could just compute two-tailed p-values as: cc <- coef(summary(fit$mer)) 2*pnorm(abs(cc[,"t value"]),lower.tail=FALSE) or 2*pnorm(-abs(cc["t value"]))
I've been using R for decades (was at MIT when Ross Ihaka has writing it) but have never joined the sigs. How do I post this reply on the R-sig-ME thread? Nick