Hi everyone, I'm having a little trouble with working out what formula is better to use for a repeated measures two way anova. I have two factors, L (five levels) and T (two levels). L and T are both crossed factors (all participants do all combinations). So, I do:
summary(aov(dat~L*T+Error(participant/(L*T)),data=dat4)) But get different results with: anova(lme(dat~L*T,random=~1|participant,data=dat4)). Rather, the lme results are the same as those with the formula summary(aov(dat~L*T+Error(participant),data=dat4)) I know most people advocate the use of lme rather than aov, but I think I need to include factors L and T in the error term and can't figure out how to do this with lme, so possibly the first aov is more correct. I have a balanced design so I don't think it would be a problem to use aov. The first aov shows an expected significant interaction (unlike lme and the second aov), but I don't want to use this if it's incorrect! If anyone could help, that would be great. -- View this message in context: http://r.789695.n4.nabble.com/AOV-LME-tp3044118p3044118.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.