similar to: treatment effect at specific time point within mixed effects model

Hi David: In looking at your original post it is a bit difficult to ascertain exactly what your null hypothesis was. That is, you want to assess whether there is a treatment effect at time 3, but compared to what. I think your second post clears this up. You should refer to pages 224- 225 of Pinhiero and Bates for your answer. This shows how to specify contrasts. > -----Original Message-----

Dear list members, I am new to R and to the R-help list. I am trying to perform a mixed-model analysis using the lmer() function. I have a problem with the output anova table when using the anova() function on the lmer output object: I only get the numerator d.f., the sum of squares and the mean squares, but not the denominator d.f., F statistics and P values. Below is a sample output, following

Dear All, I'm trying to use waldtest to test poolability (parameter stability) between two logistic regressions. Because I need to use robust standard errors (using sandwich), I cannot use anova. anova has no problems running the test, but waldtest does, indipendently of specifying vcov or not. waldtest does not appear to see that my models are nested. H0 in my case is the the vector of

Hi all, I am running the following model: > glm89.nb <- glm.nb(AvGUD ~ Year*Trt*Micro) where Year has 3 levels, Trt has 2 levels and Micro has 3 levels. However when I run it has a zero inflated negative binomial (as I have lots of zeros) I get the below error message: > Zinb <- zeroinfl(AvGUD ~ Year*Trt*Micro |1, data = AvGUD89, dist = "negbin") Error in optim(fn =

Dear R help list, I have done a lot of searching but have not been able to find an answer to my problem. I apologize in advance if this has been asked before. I am applying a mixed model to my data using lmer. I will use sample data to illustrate my question: >library(lme4) >library(arm) >data("HR", package = "SASmixed") > str(HR) 'data.frame': 120 obs.

All, I'm using lmer for some repeated measures data and have specified the contrasts for a time factor such that say time 3 is the base. This works fine. However, when I next use the subset argument to remove the last two time values, the output indicates that the specified contrast is not maintained (see below). I can solve this by creating a new dataframe for the subset of interest