Can lme allow for serial correlation and 'pure' measurement error?
Min Gong supplied me with the following (which might also work in lmer in the lme4 package): I think you are probably referring to this. He can use subject as a grouping factor when measuring the serial correlation between periods.. http://stat.ethz.ch/R-manual/R-patched/library/nlme/html/corAR1.html
On 05/30/08 10:46, Andrew Robinson wrote:
I don't think that lme can do that out of the box. One hack to get around the problem would be to use the mean of the multiple measurements, also record the standard error of measurements within examination and feed the latter into a variance model using the weights argument. I hope that this helps, Andrew On Thu, May 29, 2008 at 03:29:29PM +0100, Jonathan.Bartlett at lshtm.ac.uk wrote:
Dear mixed models list Could someone please confirm my belief that lme does not allow one to fit models with separate serial correlation and measurement error components? In SAS proc Mixed, one can use serial correlation with a "repeated", and adding the option "local" to this state adds an additional independent error term. As far as I can tell from Pinheiro and Bates, lme only allows specification of a single level of residual covariance structure. As far as I understand, a nugget effect does not give the same residual covariance structure that I want. Just to give the context, I'm analysing a dataset in which subjects are measured repeatedly over time. Subjects are measured at a number of examinations, with multiple measurements made at each examination (though not always the same number-otherwise I would just take the mean). Conditional on a set of random effects, I believe there is serial correlation, but since I have multiple measurements at identical times for each subject, I need an additional measurement error component, since for a model with just serial correlation a subject's measurements at the same time point must be identical. My apologies if the answer is obviously no, but I just wanted to check I wasn't missing something obvious. Many thanks Jonathan Bartlett [[alternative HTML version deleted]]
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