longitudinal survey data

Sorry, still confused. If I dont have fpc's ready in my dataset (calculate
myself?) that means that R will use the weight of an individual for each of his
repeated observations. But is that then still correct? The "cluster" individual
is ignored and each observation of an individual has the same weight.

Well, it depends to some extent on what inferences you are making, but 
yes, you probably do want each observation to have the same weight.

Suppose you have 4 measurements on each person, and you are working with a 
simple random sample of 1000 people from a population of 1,000,000. If you 
had done these 4 measurements on the whole population you would have 
4,000,000 measurements, so the 4000 measurements you have are 1/1000 of 
the population.  This is the same weighting as if you had a single 
measurement person person, giving 1000 measurements in the sample and 
1,000,000 in the population.

If different individuals have different numbers of measurements then 
things get a bit trickier. It depends then on why there are different 
numbers of measurements.If they are the result of non-response you might 
want to rescale the weights at later time points to give the right 
population totals.  If they are part of the sampling design then the 
design will specify what to do with them.


 	-thomas