[R] newbie polr() question

Emmanuel Charpentier charpent at bacbuc.dyndns.org
Tue Nov 27 00:50:38 CET 2007

Max a écrit :
> Prof Brian Ripley explained :
>> On Mon, 26 Nov 2007, Max wrote:
>>> Hi everyone, I'm trying to understand some R output here for ordinal
>>> regression. I have some integer data called "A" split up into 3 ordinal
>>> categories, top, middle and bottom, T, M and B respectively.
>>> I have to explain this output to people who have a very poor idea about
>>> statistics and just need to make sure I know what I'm talking about
>>> first.
>>> Here's the output:
>>> Call:
>>> polr(formula = Factor ~ A, data = a, Hess = TRUE, method = "logistic")
>>> Coefficients:
>>> Value        Std. Error  t value
>>> A -0.1259028 0.04758539  -2.645829
>>> Intercepts:
>>> Value Std. Error t value
>>> B|M -2.5872 0.5596 -4.6232
>>> M|T 0.3044 0.4864 0.6258
>>> Residual Deviance: 204.8798
>>> AIC: 210.8798
>>> I really am not sure what the intercepts mean at all. However, my
>>> understanding of the coefficient of A is that as the category
>>> increases, A decreases? If I have an A value of 10, how to I figure out
>>> the estimated probability that this score is in one of the three
>>> categories?
>> Use predict(): see the book polr supports for examples (and the theory).
> I appreciate the reply, but have difficulty understanding what you mean 
> by "the book polr supports"? :-?
> The manuals in R don't reference the polr() command, nor do they write 
> about ordinal regression in R. (from what I can tell) The documentation 
> of the polr() doesn't explain the output or the theory... I've done web 
> searches on polr() and the MASS library and have found little of direct 
> help to my question.

Brian Ripley probably means "Modern Applied Statistics with S", W
Venables and B. Ripley (4th edn), Springer, 2002. I'd also add
"Categorical Data Analysis", Alan Agresti, Wiley (2000).


					Emmanuel Charpentier

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