weighted-ML estimates
On Fri, Feb 13, 2009 at 8:55 AM, H c <harlancampbell at gmail.com> wrote:
Hi, We are trying to calculate ML-parameter estimates of a mixed effects models where the observations are weighted. The "weights" option in lmer() with RELM=FALSE seems attractive. Does anyone know the mechanism it uses to calculate weighted ML estimates?
The weights are with respect to the observations. The log-likelihood depends on a residual sum of squares in the unweighted case. In the weighted case a weighted residual sum of squares is used.
(Is there a paper?). Also, our model includes a serial correlation structure(e.g. AR(1)) among the residuals. As far as I know, no such "cor" option is available in lmer() unlike in nlme. Is this correct and if so, any suggestions on how to proceed?
You are correct. The lmer function does not incorporate serial correlation structures.