Dear R-users, I did do a thorough search and read many articles and forum threads on the lme and lmer methods and their pitfalls and problems. I, being not a good statistician but a mere "user", came to the conclusion that the most correct form of reporting statistics for a mixed linear model would be to report the parameter estimates and SEs, and, if the sample size is considerably high, p-values of a student's t-test on those.
Now, I did that in my article and I got a response from a reviewer that I additionally should give the degrees of freedom, and the F-statistics. From what I read here, that would be incorrect to do, and I sort of intuitively also understand why (at least I think I do). Well, writing on my rebuttal, I find myself being unable to explain in a few, easy to understand (and, at the same time, correct) sentences stating that it is not a good idea to report (most likely wrong) dfs and F statistics. Can somebody here help me out with a correct explanation for a laymen? Any help is dearly appreciated, Jule -- View this message in context: http://www.nabble.com/lme-and-lmer-df%27s-and-F-statistics-again-tp19835361p19835361.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
