[R] help with polytomous logistic regression

Anne
Sat, 08 Jan 2005 13:04:54 -0000

Thank you all for your help!
I tried successfully the Anova() procedure in car packagea and now am woking
on John Fox solution to display effects...

 Anne


----- Original Message -----
From: "Robert Andersen" <andersr at mcmaster.ca>
To: "Anne" <anne.piotet at urbanet.ch>
Sent: Friday, January 07, 2005 6:43 PM
Subject: RE: [R] help with polytomous logistic regression


> Dear Anne,
> I'm not sure, but I think the "anova" (which only allows you
to compare
> multinomial models that were fit separately) and "Anova" (you
only need to
> fit one model to get type II tests) functions John refers to below are not
> functional until R version 2.0 and later.
> Bob
>
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Anne
> > Sent: Friday, January 07, 2005 10:20 AM
> > To: John Fox
> > Cc: 'R list'
> > Subject: Re: [R] help with polytomous logistic regression
> >
> >
> > Thank you, John! it is exactly what I need...looking forward to apply
it
> >
> > Anne
> >
> > what would I become without this list?
> >
> >
> > ----- Original Message -----
> > From: "John Fox" <jfox at mcmaster.ca>
> > To: "'Anne'" <anne.piotet at urbanet.ch>
> > Cc: "'R list'" <r-help at stat.math.ethz.ch>
> > Sent: Friday, January 07, 2005 3:56 PM
> > Subject: RE: [R] help with polytomous logistic regression
> >
> >
> > > Dear Anne,
> > >
> > > There's an anova() method for multinom objects that will
allow
> > you to get
> > > likelihood-ratio tests. Likewise, the Anova() function in the
> > car package
> > > has a method for multinom objects.
> > >
> > > As to plotting, I have a paper, coauthored with Bob Andersen,
> > on producing
> > > "effect" plots (partial plots) for polytomous logistic
regression,
> > including
> > > multinomial and proportional-odds logistic regression. The paper,
at
> > >
> >
<http://socserv.socsci.mcmaster.ca/jfox/logit-effect-displays.pdf>, has
an
> > R
> > > function for computing such effects, including standard errors.
> > There are
> > > examples in the paper as well. Eventually, I intend to
incorporate
this
> > into
> > > the effects package to make the graphs more or less automatic.
> > >
> > > Regards,
> > >  John
> > >
> > > --------------------------------
> > > John Fox
> > > Department of Sociology
> > > McMaster University
> > > Hamilton, Ontario
> > > Canada L8S 4M4
> > > 905-525-9140x23604
> > > http://socserv.mcmaster.ca/jfox
> > > --------------------------------
> > >
> > > > -----Original Message-----
> > > > From: r-help-bounces at stat.math.ethz.ch
> > > > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
Anne
> > > > Sent: Friday, January 07, 2005 8:53 AM
> > > > To: R list
> > > > Subject: [R] help with polytomous logistic regression
> > > >
> > > > Hi!
> > > >
> > > > I'm trying to do some ploytomous logistic regression
using
> > > > multinom() in the nnet package, but am a bit confused about
> > > > interpretation of the results Is it possible to get the
> > > > following quantities:
> > > >
> > > > I:  maximum likelihood estimates to test for fit of model
and
> > > > significance of each predictor
> > > >
> > > > (I would like to produce a table of the following type)
> > > > Analysis of Variance: MLE    (values are non sensical, I
know!)
> > > >                df      chi2           p
> > > > intercept   2       57            .003
> > > > v1            4       89            .876
> > > > v2            2         7            .05
> > > > LR        110     450            0.93
> > > >
> > > > II:  chi square values and corresponding p-values for each
> > > > level of the predictor variates (I'm OK for the
estimates and
> > > > se from summary,)
> > > >
> > > >
> > > >                level estimate     se        chi2         p
> > > > intercept   1        5              .9         32
.002
> > > >                 2       6.3            .8         31
.03
> > > > v1             3       89            .876       43
.001
> > > >                 4       65            .05         67
> > > > 0.001
> > > >  v2...
> > > >
> > > >
> > > > Is there a convenient way to plot the results? (I'd like
to
> > > > display visually the effects of the predictors: any
sugestion?)
> > > >
> > > > OK, I probably miss something here (no experience with (non
> > > > ordinal) polytomous logistic regression yet!)
> > > >
> > > > Thank  very much to all
> > > >
> > > > Anne
> > > >
> > > > ----------------------------------------------------
> > > > Anne Piotet
> > > > Tel: +41 79 359 83 32 (mobile)
> > > > Email: anne.piotet at m-td.com
> > > > ---------------------------------------------------
> > > > M-TD Modelling and Technology Development PSE-C
> > > > CH-1015 Lausanne
> > > > Switzerland
> > > > Tel: +41 21 693 83 98
> > > > Fax: +41 21 646 41 33
> > > > --------------------------------------------------
> > > >
> > > > [[alternative HTML version deleted]]
> > > >
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