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H-F corr.: covariance matrix for interaction effect
2005 Feb 23
1
H-F corr.: covariance matrix for interaction effect
...- D / ((k - 1) * (N1 - N2 + N3)) epsiHF <- (n * (k-1) * epsiGG - 2) / ((k-1) * ((n-1) - (k-1)*epsiGG)) c(epsiGG,epsiHF) } # three factors, facROI,facCond,facSubj # facROI,facCond are main effects, facSubj is "repeatedness" # G-G and H-F corrections for a main effect # we do the gghf stuff for the ROI, which means ROIs in columns, # subjects in rows mtx <- NULL for (iROI in 1:length(unique( facROI ))) { for (iSubj in 1:length(unique( facSubj ))) { mtx <- c(mtx, mean(vecData[facROI==unique(facROI)[iROI] & facSubj==unique(facSubj)[iSubj]])...
H-F corr.: covariance matrix for interaction effect
2005 Feb 23
1
H-F corr.: covariance matrix for interaction effect
...- D / ((k - 1) * (N1 - N2 + N3)) epsiHF <- (n * (k-1) * epsiGG - 2) / ((k-1) * ((n-1) - (k-1)*epsiGG)) c(epsiGG,epsiHF) } # three factors, facROI,facCond,facSubj # facROI,facCond are main effects, facSubj is "repeatedness" # G-G and H-F corrections for a main effect # we do the gghf stuff for the ROI, which means ROIs in columns, # subjects in rows mtx <- NULL for (iROI in 1:length(unique( facROI ))) { for (iSubj in 1:length(unique( facSubj ))) { mtx <- c(mtx, mean(vecData[facROI==unique(facROI)[iROI] & facSubj==unique(facSubj)[iSubj]])...