Wiggin <wiggin.peters <at> gmail.com> writes: > > i am analyzing some data and have a question i hope someone can > answer. > > i want to use this sort of model: > [quoting snipped to fool gmane into letting me post a short answer] lmer( y ~ x + (1 | ID ), family=binomial, weight=w) so i want to explore the relationship between y and x, with a random effect for each patient. my question is this. is this a sensible model to use when the number of observations for each patient ID is often one? I have 305 observations for 239 patients.186 of the patients have only one observation each and another 40 have two observations each. at the other extreme, one patient has 5 observations lmer fits the model without complaining. but is this a sensible thing to do? it might be silly if so many of my patients only have on observation each. i've tried doing some reading but i cannot find an answer to this question. ========= This is really a better question for r-sig-mixed-models. Please repost there. The short answer that this is indeed sensible.
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