I would like to try multivariate multiple regression with 5 dependent variables, 3-4 independent variables. All are continuous quantitative variables and are standardized data (because some of them are not normal distribution). I searched the method for R and I tried with these model:
mmr1 <- manova(lm(cbind(Y1, Y2, Y3, Y4, Y5) ~ X1 + X2 + X3 + X4))summary(mmr1)mmr2 <- lm(cbind(Y1, Y2, Y3, Y4, Y5) ~ X1 + X2 + X3 + X4)summary(manova(mmr2))I referred to this.
I got one regression equation as result (the results were the same between them). However, I heard "manova" is used for the case that categorical variables are included and I am wondering these models is not appropriate for my case because of not including categorical variables.
Although I also read and tried this site, I see that is a repetition of multiple regression, and regression equations were obtained for each dependent variable. I would like to express the effect of independent variables on multiple dependent variables with one regression equation.
Is it possible to do this with R? And could you teach me the proper way to do this case? Thank you.
