[R] longitudinal survey data

h.brunschwig@utoronto.ca h.brunschwig at utoronto.ca
Fri May 27 16:06:07 CEST 2005

Thank you for your reply.

Does that mean that in order to take in account the repeated measures I denote
these as another cluster in R?


Quoting Thomas Lumley <tlumley at u.washington.edu>:

> On Thu, 26 May 2005 h.brunschwig at utoronto.ca wrote:
> >
> > Dear R-Users!
> >
> > Is there a possibility in R to do analyze longitudinal survey data
> (repeated
> > measures in a survey)? I know that for longitudinal data I can use lme()
> to
> > incorporate the correlation structure within individual and I know that
> there is
> > the package survey for analyzing survey data. How can I combine both? I
> am
> > trying to calculate design-based estimates. However, if I use svyglm() from
> the
> > survey package I would ignore the correlation structure of the repeated
> measures.
> >
> You *can* fit regression models to these data with svyglm(). Remember that 
> from a design-based point of view there is no such thing as a correlation 
> structure of repeated measures -- only the sampling is random, not the 
> population data.
> If you *want* to fit mixed models (eg because you are interested in 
> estimating variance components, or perhaps to gain efficiency) then it's 
> quite a bit trickier. You can't just use the sampling weights in lme(). 
> You can correct for the biased sampling if you put the variables that 
> affect the weights in as predictors in the model.  Cluster sampling could 
> perhaps then be modelled as another level of random effect.
>  	-thomas
> Thomas Lumley			Assoc. Professor, Biostatistics
> tlumley at u.washington.edu	University of Washington, Seattle

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