R help - Jun 2011 - mixed model question and using lmer

i am analyzing some data and have a question i hope someone can
answer.

i want to use this sort of model:

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.

thanks you for your advice

wiggin.

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.