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Hi, I would like to compare two models in R with the same dependant variable but different predictors (two different types of frequency and reaction times as RT). An editor told me to have a look at Lorch and Myers 1990. Lorch and Myers use the following technique: 1) they perform regressions on individual subjects' data 2) they extract the beta weights 3) they run t-test on these beta weights. The point is that I don't want to compare the "size effect" from the different models...

...;-xyplot(y ~ x | z, data,index.cond=list(order(c(1, ,6,4,3,2,5)))) or plot<-xyplot(y ~ x | z, data) plot update(plot,index.cond=list(order(c(1,6,4,3,2,5)))) I suspect it is some obvious misunderstanding of my use of list(order(...)). Thanks for any help you can give, -Pat Dr. Patrick D. Lorch plorch at email.unc.edu http://www.unc.edu/~plorch/lorch.html Department of Biology W: 919-843-2320 University of North Carolina F: 919-962-1625 at Chapel Hill CB#3280, Coker Hall Chapel Hill, NC 27599-3280 USA

...ols come out as open circles (19)). I have not messed with writing my own panel functions, though I know that is where the solution must lie. Hopefully someone has an example that is close enough to help me. I can send an example plot to anyone that wants one. Thanks, -Pat Dr. Patrick D. Lorch plorch at email.unc.edu http://www.unc.edu/~plorch/lorch.html Department of Biology W: 919-843-2320 University of North Carolina F: 919-962-1625 at Chapel Hill CB#3280, Coker Hall Chapel Hill, NC 27599-3280 USA

How does one go about doing a repeated measure regression? The documentation I have on it (Lorch & Myers 1990) says to use linear / (subj x linear) to get your F. However, if I put subject into glm or lm I can't get back a straight error term because it assumes (rightly) that subject is a nominal predictor of some sort. In looking at LME it seems like it just does the right thi...