Hi, Sorry to bother you again.
I would like to estimate the effect of several categorical factors (two between subjects and one within subjects) on two continuous dependent variables that probably covary, with subjects as a random effect. *I want to control for the covariance between those two DVs when estimating the effects of the categorical predictors** on those two DVs*. The thing is, i know the predictors have an effect on DV1, and i know DV2 covaries with DV1, so it would be "cheating" to simply estimate the effect of the predictors on DV2 because those effects could be indirect (via DV1), right ? I see two solutions : *One solution would be a mixed model MANOVA (if that even exists)*. But i don't know how to run a mixed model MANOVA, i tried to do it with Statistica but couldn't find the right module (I know how to declare two DVs and run a GLM, but *I don't know if the covariance between my two DVs is automatically controlled for*). Same thing with R. I tried to ask a question on Statistica's forum with no answer, tried looking around in the manuals with no improvement. *A backup solution would be a multiple regression* (regressing DV2 against DV1 with the categorical predictors). But i am not sure how to implement a mixed model, which function i should use and besides, it would be *much less convenient because one of my categorical predictors has three levels*(so i would have to split it and make it two predictors, right?). Thank you for any help at all ! Cheers, L. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org 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.