Dear Gary,
Stata provides facilities to analyze complex survey data, but clarify don't
incorporate corrections for survey design (except the command options
"pweight" and "cluster").
I saw a discussion on the topic in the list. There, you argue that "If you
are estimating causal effects, then you almost surely do not need the sample
weights. The only issue is if the weights are a potential omitted variable
that is causally prior to your key causal variable and correlated with it
and the dependent variable." However, my advisor recommends me to use the
svy utilities arguing that they prevent from bias and (in)efficiency. Is
there a piece to justify why I do not need sample weights? The same apply to
clustering and stratification?
Kind regards,
Javier
