This should work (with x containing the dataframe): > x$Id=factor(x$Id) > x$Group=factor(x$Group) > x$Task=factor(x$Task) > str(x) 'data.frame': 48 obs. of 4 variables: $ Id : Factor w/ 24 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ... $ Group: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ... $ Task : Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ... $ Score: num 0.39 0.48 0.59 0.33 0.38 0.37 0.47 0.2 0.29 0.41 ... > out.aov = aov(Score~Group*Task+Error(Id+Id:Task),data=x) > summary(out.aov)
Error: Id Df Sum Sq Mean Sq F value Pr(>F) Group 1 0.03420 0.03420 2.1382 0.1578 Residuals 22 0.35189 0.01600 Error: Id:Task Df Sum Sq Mean Sq F value Pr(>F) Task 1 0.048133 0.048133 5.2144 0.03242 * Group:Task 1 0.024687 0.024687 2.6743 0.11621 Residuals 22 0.203080 0.009231 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > out.aov = aov(Score~Group*Task+Error(Id),data=x) will work as well, but the error-term will be labelled simply as ``Within'', rather than as the interaction of Id*Task > > Hi, > > I have some problems with my repeated measures analysis. When I > compute it > with SPSS I get different results than with R. Probably I am doing > something > wrong in R. > I have two groups (1,2) both having to solve a task under two > conditions > (1,2). That is one between subject factor (group) and one within > subject > factor (task). I tried the following: > > aov(Score ~factor(Group)*factor(Task)+Error(Id))) > aov(Score ~factor(Group)*factor(Task)) > but it leads to different results than my spss. I definitely miss > some point > here . > > Thanks for you help. > > Id Group Task Score > 1 1 1 0.39 > 2 1 1 0.48 ______________________________________________ R-help@stat.math.ethz.ch 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.