Dear list, im facing an issue of statistical data analysis that I consider myself unable to resolve in R so i hope to get some valuable insights from you. i run an ANOVA with four factors; factor4 is an between factor (two different groups measured), the others are withins (tested across /all/ subjects). accordingly, my model looks as follows: fm1 <-aov(dataSubjects~(factor1*factor2*factor3*factor4)+Error(subject/(factor1* factor2*factor3))+factor4,data=mydata) print(summary(fm1)) so far so good. i now would like to perform multiple comparisons, but separately for each level of factor4 (two). this is how I do it: i sort out (using subset) the levels im interested in comparing, say level 1 of factor 1 Type.lvl1 <- subset(mydata, factor1 == "lvl1") and then compute an uncorrected pairwise t-test between the two levels of factor 4: Type.lvl1.P<-pairwise.t.test(Type.lvl1$dataSubjects,Type.lvl1$factor4,p.adj = "none") i do this for every comparison im interested in and apply any method for multiple comparison correction afterwards on the entire set of p values obtained. is this valid (in statistical terms)? if not, could anyone refer to a better procedure i should use instead? Thanks in advance. Lisa
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