[R-sig-ME] Weighting analysis in Lme4

[Ben Bolker]

  Hopefully someone else will respond as well, but:

  As I understand it combining survey weighting with lme4's
regression-based approach is tricky.  lme4's weights argument does *not*
(again as I understand it, this isn't my area) correspond to sample weights.

If you google "site://stat.ethz.ch/pipermail/r-sig-mixed-models/ survey
weights" you'll find a lot of discussion on the list, e.g.

https://stat.ethz.ch/pipermail/r-sig-mixed-models/2014q4/022795.html

  Anyone have any new insights into this problem?

  Ben B.

On 16-12-08 03:25 PM, justine briaux wrote:
>  Dear Mr Bolker,
> 
> I am a PHD student in Public Health and I am currently working on data
> collected with a  complex survey design. These data were collected in 5
> different districts/ strata (codpref) and 162 villages/cluster (numvill).
> In each village a representative sample of mother-infant pairs was
> surveyed. Some mother-infant pairs come from the same household (household=
> idmen).
> In order to consider those three interlocked levels I've done mixed model
> using the lme4 package in R
> 
> glmer(undernutrition~household food insecurity+(1|codpref)+(1|numv
> ill)+(1|idmen),data=menme,family=binomial)
> 
> I am wondering if I should weight my analysis in order to take into account
> the survey weights (pond) as the "survey package" would have done it.
> 
> I saw in the R documentation that the argument "weight" exist in the lme4
> package, does it correspond to survey weights? For instance, would it be
> correct to write:
> 
>  glmer(undernutrition~household food
> insecurity+(1|codpref)+(1|numvill)+(1|idmen),data=menme,
> weight= pond, family=binomial)
> 
> I wanted to use the survey package but it does not allow me to do a mixed
> model and thus to take into accound the household level (idmen).
> 
> I am really confused. What should I do?
> 
> 
> Thanks a lot for your help.
> Looking forward to hearing from you.
> 
> Warm regards.
> 
> Justine Briaux
> PHD student
> IRD, France
> 
> <r-sig-mixed-models at r-project.org>
> 
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> 
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