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I'm using the svydesign package in R to run survey weighted logit regressions as follows:

sdobj <- svydesign(id = ~0, weights = ~chweight, strata = ~strata, data = svdat)

model1 <- svyglm(formula=formula1,design=sdobj,family = quasibinomial)

However, the documentation states a caveat about regressions without specifying finite population corrections (FPC):

    If fpc is not specified then sampling is assumed to be
with replacement at the top level and only the first stage of
 cluster is used in computing variances.

Unfortunately, I do not have sufficient information to specify my populations at each level (of which I sampling very little). Any information on how to specify survey weights without FPC information would be very helpful.

mike
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1 Answers1

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You're doing it right. "With replacement" is survey statistics jargon for what you want in this case.

If the sampling fraction is low, it is standard to use an approximation that would be exact if the sampling fraction were infinitesimal or sampling were with replacement. No-one actually does surveys with replacement, but the approximation is almost universal. With this approximation you don't need to supply fpc, and conversely, if you don't supply fpc, svydesign() assumes you want this approximation.

Thomas Lumley
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