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:[EMAIL PROTECTED] Sent: 07 May 2004 15:07 To: Jacqueline Hall Cc: [EMAIL PROTECTED] 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, [EMAIL PROTECTED] 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 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
