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 but how well the two models fit. So my idea was to extract the correlation coefficients instead of betas and doing t-tests on these. I checked and my correlation coefficients are normally distributed... Is it ok to do that? Best regards, [[alternative HTML version deleted]] ______________________________________________ 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.