search for: var00001

... and is there also such a nice tool (like spss.get) for exporting data frames to SPSS? write.table does not keep the data frame labels - neither did the other exporting tools that I found. Thanks! Michael [[alternative HTML version deleted]]

I am running a multi-level model. I use the following commands with validatedRS6 as the outcome, random as the predictor and clustno as the random effects variable. new<-as.data.frame(read.delim("BABEX.dat", header=TRUE)) install.packages("lme4") library(lme4) model1<- glmer(validatedRS6 ~ random + (1|clustno), data=new, family=binomial("logit"), nAGQ)

...Subjects/( color*shape) ) In spss you would have something like this (of course with the data organized slightly differently : GLM x1 x2 x3 x4 BY MyGroup /WSFACTOR = color 2 Polynomial shape 2 Polynomial /METHOD = SSTYPE(3) /CRITERIA = ALPHA(.05) /WSDESIGN = color shape color*shape /DESIGN = VAR00001 . Ok, the question is. If the group sizes are different (say 10 people in one group and 12 people in the other group) R is going to give the wrong answer. Of course that is not R's fault. BUT MY QUESTION IS: HOW TO GET THE UNBALANCED REPEATED MEASURES ANOVA RIGHT? Thanks for the answer!

...350203 -0.32664493 0.68958988 0.15612729 13 14 15 16 17 18 -3.10081497 -1.43820259 2.20031311 0.86156818 -0.29869392 0.49171093 19 20 21 1.02517352 1.61796106 -10.50956979 (Intercept) VAR00001 VAR00002 VAR00003 -41.5230433 0.9388404 0.5794524 -0.1129150 I am very worried by this discrepancy what have I done wrong? I read in R:Robust Fitting of Linear Models: MM estimation is M-Estimation with Tukey's biweight initialized by a specific S-estimator and so I alter my S-Plu...

read.spss() is giving "Rgui.exe has generated errors and will be closed..." on all the files I have tried (the same happens with Rterm as well). This is R1.3.0 and the current `foreign',under Win2k. The problem doesn't happen under Linux on a different machine and didn't happen with an earlier version of R and foreign under NT4 on a different machine. As I updated to a new

...ror( Subjects/( color*shape) ) In spss you would have something like this (of course with the data organized slightly differently : GLM x1 x2 x3 x4 BY MyGroup /WSFACTOR = color 2 Polynomial shape 2 Polynomial /METHOD = SSTYPE(3) /CRITERIA = ALPHA(.05) /WSDESIGN = color shape color*shape /DESIGN = VAR00001 . Ok, the question is. If the group sizes are different (say 10 people in one group and 12 people in the other group) R is going to give the wrong answer. Of course that is not R's fault. === message truncated === __________________________________________________ [[alternative HTML ve...