On 9/25/05, Horacio Montenegro <[EMAIL PROTECTED]> wrote: > > Hi Spencer and Robert, > > I have found the same behaviour, but only for lme4 > and Matrix after the 0.96 release. lme4 0.95-10 and > Matrix 0.95-13 releases gave "sensible" results. This > could be an introduced bug, or a solved bug - you > should ask Prof. Bates. > > hope this helps, cheers, > > Horacio Montenegro
I have run into a couple of other things that the "improvements" from the 0.95 series to the 0.96 series has made worse. This may take a while to sort out. Thanks to Robert Bagchi for the very thorough error report. > > --- Spencer Graves <[EMAIL PROTECTED]> wrote: > > I agree: Something looks strange to me in this > > example also; I have > > therefore copied Douglas Bates and Deepayan Sarkar. > > You've provided a > > nice simulation. If either of them have time to > > look at this, I think > > they could tell us what is happening here. > > > > If you need an answer to your particular problem, > > you could run that > > simulation 1000 or 1,000 times. That would tell you > > whether to believe > > the summary or the anova, or neither. If you want > > to understand the > > algorithm, you could walk through the code. > > However, "lmer" is a > > generic, and I don't have time now to figure out how > > to find the source. > > A response from Brian Ripley to a question from me > > a couple of days > > ago provides a nice summary of how to do that, but I > > don't have time to > > check that now. > > > > Sorry I couldn't help more. > > spencer graves > > > > Robert Bagchi wrote: > > > > > Dear R users, > > > > > > I have been having problems getting believable > > estimates from anova on a > > > model fit from lmer. I get the impression that F > > is being greatly > > > underestimated, as can be seen by running the > > example I have given below. > > > > > > First an explanation of what I'm trying to do. I > > am trying to fit a glmm > > > with binomial errors to some data. The experiment > > involves 10 > > > shadehouses, divided between 2 light treatments > > (high, low). Within each > > > shadehouse there are 12 seedlings of each of 2 > > species (hn & sl). 3 > > > damage treatments (0, 0.1, 0.25 leaf area removal) > > were applied to the > > > seedlings (at random) so that there are 4 > > seedlings of each > > > species*damage treatment in each shadehouse. > > There maybe a shadehouse > > > effect, so I need to include it as a random > > effect. Light is applied to > > > a shadehouse, so it is outer to shadehouse. The > > other 2 factors are > > > inner to shadehouse. > > > > > > We want to assess if light, damage and species > > affect survival of > > > seedlings. To test this I fitted a binomial mixed > > effects model with > > > lmer (actually with quasibinomial errors). THe > > summary function suggests > > > a large effect of both light and species (which > > agrees with graphical > > > analysis). However, anova produces F values close > > to 0 and p values > > > close to 1 (see example below). > > > > > > Is this a bug, or am I doing something > > fundamentally wrong? If anova > > > doesn't work with lmer is there a way to perform > > hypothesis tests on > > > fixed effects in an lmer model? I was going to > > just delete terms and > > > then do liklihood ratio tests, but according to > > Pinheiro & Bates (p. 87) > > > that's very untrustworthy. Any suggestions? > > > > > > I'm using R 2.1.1 on windows XP and lme4 0.98-1 > > > > > > Any help will be much appreciated. > > > > > > many thanks > > > Robert > > > > > > > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html