multilevel analysis with sample weighted data

On 14-08-28 07:01 AM, Rodrigo Travitzki wrote:

Dear R masters,
I'm looking for a R package to do multilevel analysis of a weighted data
(is a weigthed sample of brazilian educational data) but could not find
it. There is just a "weights" option in lme(), but is not about
frequency (or probability) weigths in data. In some foruns, no response
either.
So, could you please confirm this information for me? There is any R
package/function which do this? I really don't want to use proprietary
software, but if there is no option, I'll need to do so.
Thank you very much.

Best wishes,
Rodrigo Travitzki

   It depends a little bit what you want to do/the meaning of the
weights.  I have successfully used weights=varFixed(~I(1/n))
[inverse-variance weighting based on the number of samples per group] in
lme; alternatively, you could use weights=n in lmer (from the lme4
package) to get an equivalent result.

If you want to deal with survey weighting, the story seems to be
considerably more complicated -- I don't claim to understand it, but
Andrew Gelman (a fairly prominent applied Bayesian statistician) claims
that it's "a mess" (to use his phrase).  If the weights represent
probability of inclusion in a survey, I believe he would recommend
model-based inference -- that is, fit an unweighted multilevel
regression model and then use post-stratification/weighting to make
predictions (see http://andrewgelman.com/?s=survey+weights for various
discussion and links to papers).

   good luck,
     Ben Bolker