longitudinal survey data

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