search for: roidataframe

...ueR <- rowMeans( LHroi.cueR[,t1:t2] ) rh_cueL <- rowMeans( RHroi.cueL[,t1:t2] ) rh_cueR <- rowMeans( RHroi.cueR[,t1:t2] ) roiValues <- c( lh_cueL, lh_cueR, rh_cueL, rh_cueR ) cuelabels <- c("CueLeft", "CueRight") hemlabels <- c("LH", "RH") roiDataframe <- data.frame( roi=roiValues, Subject=gl(8,1,32,subjectlabels), Hemisphere=gl(2,16,32,hemlabels), Cue=gl(2,8,32,cuelabels) ) roi.aov <- aov(roi ~ (Cue*Hemisphere) + Error(Subject/(Cue*Hemisphere)), data=roiDataframe) print(summary(roi.aov)) ######################################## I'...

...I see this error? > library(stats) > require(stats) [1] TRUE > > tHSD <- TukeyHSD(aov) Error in TukeyHSD(aov) : no applicable method for "TukeyHSD" In case it helps: > aov Call: aov(formula = roi ~ (Cue * Hemisphere) + Error(Subject/(Cue * Hemisphere)), data = roiDataframe) Grand Mean: 8.195069 Stratum 1: Subject Terms: Residuals Sum of Squares 645.7444 Deg. of Freedom 7 Residual standard error: 9.604645 Stratum 2: Subject:Cue Terms: Cue Residuals Sum of Squares 0.386987 4.015740 Deg. of Freedom 1...

...now that I don't have the non-sphericity test and correction factors. The backgroud to this question is that I'm doing a psychophysics experiment and the data analysis uses an aov model that looks like this: roiAOV <- aov( roi ~ (Cue*Hemisphere) + Error(Subject/ (Cue*Hemisphere)), data=roiDataframe) where Cue is 2 levels (an arrow on a screen that points left or right) and Hemisphere is 2 levels (brain activity in the left or right cerebral hemisphere). There are 8 subjects and they all have one observation for all levels of Cue * Hemisphere (ie, a within-subjects design). I need some func...