Hello,
How should I take into account sampling weights when using -psmatch- command (or one-to-one matching based on a propensity score, in
general)?
I have a survey data where both treated and non-treated observations come from a larger population of unemployed people with
different sampling weights.
1) Should I use the sampling weights when estimating a propensity score (with a logit model, for example)? Should I use -svylogit-?
2) And how should I use the sampling weights when trying to generalise my results to the population?
Any hints or references to literature?
Thanks,
Andres Vork
PhD student in Economics
Estonia
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