glmer with non integer weights

So your respons variable behaves like a continuous variable except that
is range is limited to the 0-1 interval. In such a case I would
transform the respons variable (e.g. logit, sqrt(arcsin())) and use a
gaussian model.

A logit-Normal has variance roughly mu^2(1-mu)^2 and a quasibinomial logistic uses mu(1-mu),  with the parameters having the same interpretations. The question of which variance function best approximates the data should really be an empirical one, not an a prioiri one.  There is an example of exactly this in the quasilikelihood chapter in McCullagh and Nelder, where the observations are the proportion of damage on a set of leaves.

   -thomas

Thomas Lumley			Assoc. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle