[R-sig-ME] Fixed vs random effects with lme4
jdpo223 @ending from g@uky@edu
Thu Aug 23 17:43:17 CEST 2018
Peter Westfall wrote up how to do it in an example script
Please be aware that the test does not imply that you shouldn't use random
effects if there is correlation between a group-varying intercept and a
lower level variable. It just means that you need to do something to
properly model that correlation. That could be a within-group only model
with dummy variables for groups (standard Fixed Effects models) or a
group-mean centered model a la much of multilevel modeling. In econ this is
known as a Hausman Taylor model (yes, the same Hausman as the test) or a
correlated random effects model. You could also use a random slopes model
to allow the variability in Xi across groups but it's less effective at
debiasing than the other choices.
On Thu, Aug 23, 2018 at 11:09 AM Yashree Mehta <yashree19 using gmail.com> wrote:
> Is there a way to conduct the Hausman test on models which have been
> estimated using lme4?
> To be more specific,
> My model assumption is that the plot size(X covariate) is correlated with
> the random intercept ( estimated from Household_ID) which will be
> estimated. So I have to find out how to tell lmer to consider this
> correlation. I would also, similarly, want to carry random effects where
> this correlation assumption is done away with. Finally, I want to conduct
> the Hausman test for model choice.
> Thank you,
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> R-sig-mixed-models using r-project.org mailing list
John Poe, Ph.D.
Postdoctoral Scholar / Research Methodologist
Center for Public Health Services & Systems Research
University of Kentucky
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