I have some dependent variables related to the growth of a company having categories like (e.g. for variables indicating net profit, financial turnover etc.)
(1) decreasing,
(2) stable,
(3) increasing and
(4) rapidly increasing.
Now these variables are associated and ordinal in nature. I want to see the effect of a set of co-variates on these dependent variables. I understand that separate logistic regression will result in wrong formula of the variance and thus will produce wrong p-values. But what kind of regression should I run with more than one associated dependent categorical variables? Should that be a GEE model? Or anything else like multivariate regression (GLM)?
Can SPSS or R perform this?
Besides, I would like to have your suggestion regarding whether I should rather consider these variables as nominal and take "stable" as the reference category so that interpretations are more meaningful?
Kind regards.
(1) decreasing,
(2) stable,
(3) increasing and
(4) rapidly increasing.
Now these variables are associated and ordinal in nature. I want to see the effect of a set of co-variates on these dependent variables. I understand that separate logistic regression will result in wrong formula of the variance and thus will produce wrong p-values. But what kind of regression should I run with more than one associated dependent categorical variables? Should that be a GEE model? Or anything else like multivariate regression (GLM)?
Can SPSS or R perform this?
Besides, I would like to have your suggestion regarding whether I should rather consider these variables as nominal and take "stable" as the reference category so that interpretations are more meaningful?
Kind regards.