I forgot to cc: the list on this reply. ---------- Forwarded message ---------- From: Douglas Bates <bates at stat.wisc.edu> Date: Thu, Sep 27, 2012 at 3:54 PM Subject: Re: cross-classified random effects model R code for empirical bayes To: Webster Kasongo <kasongster at yahoo.com> It is better to send questions like this to the R-SIG-Mixed-Models at R-project.org mailing list (see https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models for more information) than to me directly. Several of those who read that list can respond to you and often do so much more quickly than I am able to.
On Thu, Sep 27, 2012 at 3:38 PM, Webster Kasongo <kasongster at yahoo.com> wrote:
Dear Dr. Bates I am womdering whether there is a way of specifying the parameter estimation method for empirical bayes method e.g., summary(fit.T2 <-lmer(wordsum ~ race+GENDER+ age+ I(age^2)+ educ+ (1|PERIOD)+(1|COHORT), data=GSSBCFINAL, REML=FALSE)) In the above code, estimation method is ML.
How can one estimate emprical bayesian method?
A facetious answer would be "learn to program in R". :-) I don't know of any R packages that provide empirical Bayes estimates. In fact, I'm not sure that the name "empirical Bayes" is sufficient to define a particular estimation method. I think it refers to a general approach and you would need to be more specific about the criterion.