Re: [R] GLM Logit and coefficient testing (linear combination)

From: John Fox <jfox_at_mcmaster.ca>
Date: Mon 19 Dec 2005 - 04:46:28 EST


Dear David,

The linear.hypothesis() function in the car package will compute a Wald test for this hypothesis, but a LR test is probably a better idea for a logit model. You can do that by fitting the restricted model and comparing that with the unrestricted model via anova().

I hope this helps,
 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@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of David
> STADELMANN
> Sent: Sunday, December 18, 2005 11:32 AM
> To: r-help@stat.math.ethz.ch
> Subject: [R] GLM Logit and coefficient testing (linear combination)
>
> Hi,
>
> I am running glm logit regressions with R and I would like to
> test a linear combination of coefficients (H0: beta1=beta2 against H1:
> beta1<>beta2). Is there a package for such a test or how can
> I perform it otherwise (perhaps with logLik() ???)?
>
> Additionally I was wondering if there was no routine to
> calculate pseudo R2s for logit regressions. Currently I am
> calculating the pseudo R2 by comparing the maximum value of
> the log-Likelihood-function of the fitted model with the
> maximum log-likelihood-function of a model containing only a

> constant. Any better ideas?
>
> Thanks a lot for your help.
> David
>
> ######################################
> David Stadelmann
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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Mon Dec 19 04:52:56 2005

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