Karen,
One way to approach this problem is to investigate the magnitude of
influence of the complex-sample weights [pweight=varname] on model
coefficients. You can do this by running --logistic ..., robust
cluster[clusname]. (The robust/cluster option is needed only if you have
cluster-sampled data.) Run the model with and without [pweight], and compare
coefficients between weighted and unweighted models. If, as is often the
case, the two are close (no rule for "close", subjective judgment based on
the end-use of your model), you might consider using unweighted logistic
modeling to obtain an approximation of R^2.
I've never had to use the svy commands myself, but people who have tell me
it hasn't made a whole lot of difference whether they do things the "right"
way or the "wrong" way. Obviously, a few anecdotal cases do not constitute
a proof, but I'd be curious to hear if this was fairly typical or if there
were instances where using the svy commands made a clear and dramatic
difference.
