Best method of analysis of multiple dependent variables in JMP
Sep 24, 2013 11:37 AM(1236 views)
I need a predictive model for two response variables (that are dependent on each other) and multiple independent variables. I'm not very statistics-savvy but am comfortable with multiple regression; however, I'm not sure of the best way to approach a problem with multiple dependent variables. I've been studying some of the approaches (MANOVA, MANCOVA, multivariate multiple regression, structural equation modeling), but I'm not sure which would be the best approach for this situation. Also, I'm limited to JMP (and the Fit Model Platform), which seems to limit some of the approaches I can use. I could possibly purchase the SEM add-on, if that would get me the best results.
I would like any advice as to which of these methods would be best-suited for my problem especially the pros/cons of the various approaches. Any literature that could point me in the right direction would be appreciated, also.