RE: [R] scores from multinomial logistic regression

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From: Jacqueline Hall (j.hall@beatson.gla.ac.uk)
Date: Sat 08 May 2004 - 01:25:11 EST


Message-id: <000301c43447$7ca72e30$62e8d182@o1jh>

Hi,

Sorry for not making this clear,

By "score" I meant the score from the score test, for assessing the addition
of a new variable to the model. (first derivative of the log likeihood/
information matrix, the ratio (score)having a chi squared distribution of
appropriate df)

I'm looking for something similar/appropraite for logistic regression, my
outcome (response) variable has 4 categories (hence the interest in
multinom), the covariates are continuous.

Thanks again,

Jacqui

-----Original Message-----
From: Prof Brian Ripley [mailto:ripley@stats.ox.ac.uk]
Sent: 07 May 2004 15:07
To: Jacqueline Hall
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] scores from multinomial logistic regression

What do you mean by the scores?

What multinom does is to fit probabilities (which you can extract by
fitted()): the response is a discrete probability distribution. There is an
underlying linear predictor but

(a) it is K-dimensional and
(b) there is a degree of ambiguity, usually resolved by setting the
predictor for one category to zero (but not in this code).

That linear predictor is only generated in the underlying C code.

On Fri, 7 May 2004, Jacqueline Hall wrote:

> Dear all,
>
> I'm interested in extracting the score from multinomial logistic
> regression models fit using multinom, to assess the stregth of
> assocation of the parameter with the response (akin to the score from
> clogit/cox regression). currently I'm using R 1.8.1. Is there a
> function that will extract the score from a multinom object or how i
> can get back to it? or from using glm? I investigated the documention
> for Design but those functions seem to apply to binary logistic.

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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