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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