Dear list, I'm trying to calculate a regression on a dataset with repeated measures. I tried to look for an example on the web and in Pinheiro and Bates "Mixed-Effects Models in .. " book. However, I' m not sure wether the regression model I'm using is the "right" one. I'm very thankful for any suggestions! Ok, here's what I'm trying to do: First, the experimental design: We ran a study, where 36 subjects played a game, where they could 150 times make risky decisions. Throughout the game we recorded physiological data. Thus, each subject made in every trial a more or less risky decision. Now, I'm interested, whether parameters of the physiological data (Phys1, Phys2) can predict the amount of risk taken by a subject.
So far my regression model looks as follows: lme(Risk ~ Phys1 + Phys2, random = ~ 1 | Subject) Could this be suitable? Is it a problem, if the Variable Risk is autocorrelated within Subjects? Thank you very much for any help and sorry if this is a too trivial question for the list. Kind regards Andreas Pedroni ______________________________________________ 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.
