From ripley@stats.ox.ac.uk  Mon Jan 27 19:16:16 2003
From: ripley@stats.ox.ac.uk (ripley@stats.ox.ac.uk)
Date: Mon Jan 27 19:16:16 2003
Subject: [Rd] help page for anova.glm/variation between S-PLUS and R
 behavior
In-Reply-To: <Pine.LNX.4.44.0301271249080.17354-100000@bolker.zoo.ufl.edu>
Message-ID: <Pine.LNX.4.44.0301271804320.17520-100000@gannet.stats>

Not really!

I don't think it is our job to describe the inconsistencies of S-PLUS,
especially since that might change from version to version. It would be
really messy, as S-PLUS ignores the scale for the Chisq test (which seems
perverse), and lacks the dispersion argument.

On Mon, 27 Jan 2003, Ben Bolker wrote:

> 
>    When using test="F" in stat.anova() / anova.glm(), R uses the assumed 
> dispersion parameter for the specified family (e.g. scale=1 for binomial), 
> while S-PLUS automatically uses the estimated dispersion parameter 
> (residual deviance/residual df).  I think there are good reasons for the 
> behavior in R -- it fits with the "you get what you actually asked for" 
> philosophy -- and there are hints in the documentation (anova.glm(): "for 
> [models] with dispersion estimated by moments ... the F test is most 
> appropriate"; family/binomial(): "The behaviour of S-PLUS is closer to the 
> quasi- variants").
>    Would R-core consider it reasonable to add yet another sentence to the
> anova.glm() documentation, e.g. after the "... F test is most appropriate"  
> sentence above, adding: "(Note: unlike R, S-PLUS automatically uses the
> moment-estimated dispersion for F-tests even for the binomial and Poisson
> families:  see ?quasibinomial.)"  ?
> 
>   Ben Bolker
> 
> 

-- 
Brian D. Ripley,                  ripley@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



[Rd] help page for anova.glm/variation between S-PLUS and R behavior
ripley@stats.ox.ac.uk