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scores from multinomial logistic regression
4 messages · Jacqueline Hall, Brian Ripley
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 at 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
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 at stats.ox.ac.uk] Sent: 07 May 2004 15:07 To: Jacqueline Hall Cc: r-help at 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 at 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
Note the coxph docs call these `efficient scores', which helps. However, what the `score' part of a coxph object gives is not the score for the addition of a new variable, but for the addition of all the variables, as I understand it. (You could do repeated fits using init=, but that's not what you said.) I am not aware of a good way to do that even for a glm. (Smart people could make add1.lm do it, I guess.) I would just do likelihood ratio tests since computation time is unlikely to be an issue these days.
On Fri, 7 May 2004, Jacqueline Hall wrote:
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 at stats.ox.ac.uk] Sent: 07 May 2004 15:07 To: Jacqueline Hall Cc: r-help at 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 at 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