On Jun 12, 2011, at 07:54 , <bill.venab...@csiro.au> <bill.venab...@csiro.au> 
wrote:

> The score test looks at the effect of adding extra columns to the model 
> matrix.  The function glm.scoretest takes the fitted model object as the 
> first argument and the extra column, or columns, as the second argument.  
> Your x2 argument has length only 3.  Is this really what you want?  I would 
> have expected you need to specify a vector of length nrow(DF), [as in the 
> help information for glm.scoretest itself].
> 

glm.scoretest will only do single-df tests, so it's not going to help here. 

Notice that the test requested is a whole-model test, i.e. a comparison of the 
fitted model with an intercept-only model (AKA a null model). It is not a 
goodness of fit test (which is a good thing as those are often dubious with 
binary responses). In R-devel, we can do score tests for such model comparisons 
as follows:

> mod2<-glm(reading.recommendation~1,family=binomial,data=DF)
> anova(mod1,mod2,test="Rao")
Analysis of Deviance Table

Model 1: reading.recommendation ~ reading.score + gender
Model 2: reading.recommendation ~ 1
  Resid. Df Resid. Dev Df Deviance   Rao Pr(>Chi)   
1       186     224.64                              
2       188     234.67 -2  -10.033 -9.53 0.008523 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

This is pretty close to the cited SAS result. I cannot tell where the .01 
discrepancy creeps in, but the GLM algorithm is not 1-step convergent for the 
null model, even though the solution can be written down explicitly.  (I don't 
have SAS to hand, but if anyone does, it would be interesting to see if it 
still says 9.5177 with the same data). 


With the current R, the closest you get is the asymptotically equivalent LRT:

> anova(mod1,mod2,test="Chisq")
Analysis of Deviance Table

Model 1: reading.recommendation ~ reading.score + gender
Model 2: reading.recommendation ~ 1
  Resid. Df Resid. Dev Df Deviance Pr(>Chi)   
1       186     224.64                        
2       188     234.67 -2  -10.033 0.006626 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 


-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk  Priv: pda...@gmail.com

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to