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

John Fox jfox at mcmaster.ca
Sun Dec 18 18:46:28 CET 2005


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 at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of David 
> STADELMANN
> Sent: Sunday, December 18, 2005 11:32 AM
> To: r-help at 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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