[R] lsmeans

[John Fox]

Dear Hadley,

Actually, the effects package does exactly what you suggest for continuous
predictors.

Regards,
 John

------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
> Behalf Of hadley wickham
> Sent: June-08-08 3:48 PM
> To: Frank E Harrell Jr
> Cc: John Fox; Douglas Bates; r-help at stat.math.ethz.ch; Dieter Menne
> Subject: Re: [R] lsmeans
> 
> > Well put Doug.  I would add another condition, which I don't know how to
> > state precisely.  The settings for the other terms, which are usually
> > marginal medians, modes, or means, must make sense when considered
jointly.
> >  Frequently when all adjustment covariates are set to overall marginal
> means
> > the resulting "subject" is very atypical.
> >
> > To me much of the problem is solved one one develops a liking for
predicted
> > values and differences in them.
> 
> Maybe I'm still misunderstanding, but isn't that exactly what effects
> displays are?  They're just some way to allow you to say, I'm
> interested in variables x, y and z, and I don't really care about the
> other variables in the model - what are some typical predictions?
> 
> The effects package implements this idea for categorical x, y, and z,
> but the basic idea remains the same for continuous variables - except
> instead of using all the levels of the factor, you'd use a grid within
> the range of the data.
> 
> Hadley
> 
> 
> --
> http://had.co.nz/
> 
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