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the study design of the data I have to analyse is simple. There is 1 control group (CTRL) and 2 different treatment groups (TREAT_1 and TREAT_2). The data also includes 2 covariates COV1 and COV2. I have been asked to check if there is a linear or quadratic treatment effect in the data. I created a dummy data set to explain my situation: df1 <- data.frame( Observation =

Hi, from what I understand about the canonical correlation function 'cancor', it looks for correlations in two sets of variables, each represented in matrix form. Right? Sounds exactly like what I need. I have tried the following but I am not sure how to interpret the results. AudioPCs <- c(ArTHarF0PCA$x[,2], ArTHarF1PCA$x[,2], ArTHarF2PCA$x[,2], ArTHarF3PCA$x[,2],

Hi Peter, You didn't give a very specific example, but it seems to me that what you wish to do is not really complicated. I suppose you have created a table of sequences vs. say hyprophobicity, charge, etc..., something like... seq hydroph arom b0001 0.104762 0.000000 b0002 0.035122 0.065854 b0003 0.024193 0.070968 b0004 -0.096729 0.084112 b0005 -0.973469 0.091837 b0006