I have two ordinal dependent variables, each having three response levels. You can use an ordered logit or probit model for such data if you have one dependent variable. I've seen some papers about multivariate ordered regression, and wonder if there are prepackaged functions in any of the usual stats software environments to do this. I am most proficient in R and Stata. Thank you.


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I am not aware of any default functions in R that run cumulative link models. Also, to the best of my knowledge, there is no subtle difference in extending univariate models to multivariate ones as far as the details of computation or interpretation of effects; everything is exactly analogous to other R linear models: use a formula function, interpret effects, and call it good. Unless you provide examples of which code you're using, I'm not too sure your problem is really a problem!

The MASS package has polr which is very nice. I am fond of the lrm function in Frank Harrel's rms package as it conveniently calculates sandwich based robust errors.


It's an old question but I bumped onto it.

Packages in R are "ordinal" by Christensen. There used to be polr but that does not work with recent R versions.

I'd use ordinal which is quite convenient with good documentation.

  • 1
    $\begingroup$ What do you mean? I have R 3.1.2 and polr in the MASS package runs just fine. $\endgroup$ – AdamO Mar 2 '15 at 20:14

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