Dear everybody! My fixed-effects-only model looks like this: glmer(Accuracy ~ C.RT*Group, data = da)
C.RT is the reaction time variable, and Group is a categorical variable with 0 and 1 as values. I would like to specify that main intercept, Group intercept, C.RT slope and C.RT*Group slope vary across subjects and trials. All subjects have values in Group = 0 and in Group = 1. Trials are nested within Group because each trial belongs either to Group = 0 or Group = 1. How should I specify the model? My ideas were: 1. glmer(Accuracy ~ C.RT*Group + (C.RT*Group|subject) + (1+C.RT|trial), data = da) or 2. glmer(Accuracy ~ C.RT*Group + (1+C.RT|Group:subject) + (1+C.RT|Group:trial), data = da) Here, Group:trial does not make much sense as trials are *per se* divided in Group 0 or Group 1. What is, in your opinion, the best way to specify the model that I want to test? Additionally, the difference between (1+C.RT|Group:subject) and (C.RT*Object|subject) is not clear to me. Can someone also shed some light here? Thanks, Dominik! [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.