Hello again S-news-ers,
After reading articles, help files, s-news and R archives, and, of course
V&R, I'm starting to understand regression with an ordinal response
variable. But I have a question (which may demonstrate that I really
don't understand regression with an ordinal response variable)...
I have an ordinal variable with 5 levels (e.g., high, medium-high, medium,
medium-low, and low) and 2 independent continuous variables.
Proportional odds logistic regression (e.g., polr() or lrm()) assumes that
the effect of each independent variable is constant across the 5 levels
of the ordinal dependent variable. Which, as I understand it, is at the
heart of the proportional odds assumption.
Multinomial logit models (e.g., multinom()) allows the effect of the
independent variables to differ across the levels of the categorical
dependent variable, but does not use the information that our dependent
variable is an ordered response.
Is there something out there in S-plus that I could use when the
proportional odds assumption is violated that has the flexibility of the
multinomial logit (with different effects sizes by level) but still
accounts for the fact that I've got an ordered dependent variable? I feel
like I must be missing or not understanding something.
Thank you for your help!
Cheers,
Andy
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"What if the Hokey Pokey is all it really is about?" - Jimmy Buffett
Andrew B. Cooper, Ph.D.
Department of Natural Resources
Nesmith Hall, Rm 208A
University of New Hampshire
Durham, NH 03824
andrew.cooper@unh.edu
603.862.4254, 603.862.4976 (FAX)
http://www.unh.edu/natural-resources/fac-cooper.html
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