[R] Weird SEs with effect()

[John Fox]

Dear Gustaf,

>From ?effect, "se: a vector of standard errors for the effect, on the scale
of the linear predictor." Does that help?

Regards,
 John

--------------------------------
John Fox, Professor
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 r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Gustaf Granath
> Sent: February-16-08 11:43 AM
> To: r-help at r-project.org
> Subject: [R] Weird SEs with effect()
> 
> Hi all,
> 
> Im a little bit confused concerning the effect() command, effects
> package.
> I have done several glm models with family=quasipoisson:
> 
> model <-glm(Y~X+Q+Z,family=quasipoisson)
> 
> and then used
> 
> results.effects <-effect("X",model,se=TRUE)
> 
> to get the "adjusted means". I am aware about the debate concerning
> adjusted means, but you guys just have to trust me - it makes sense
> for me.
> Now I want standard error for these means.
> 
> results.effects$se
> 
> gives me standard error, but it is now it starts to get confusing. The
> given standard errors are very very very small - not realistic. I
> thought that maybe these standard errors are not back transformed so I
> used exp() and then the standard errors became realistic. However, for
> one of my glm models with quasipoisson the standard errors make kind
> of sense without using exp() and gets way to big if I use exp(). To be
> honest, I get the feeling that Im on the wrong track here.
> 
> Basically, I want to know how SE is calculated in effect() (all I know
> is that the reported standard errors are for the fitted values) and if
> anyone knows what is going on here.
> 
> Regards,
> 
> Gustaf Granath
> 
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