Here a great summary on matching:
http://www.biostat.jhsph.edu/~estuart/Stuart-MatchingMethods-StatSci-Dec09.pdf
You can use as many variables as you want in your algorithm to find the
best balanced sample. Once you have it, use those weights and run
regression models with all the covariates again to adjust for the
remaining bias.
See this advice in page 537
Matthew Blackwell, Stefano Iacus, Gary King, Giuseppe Porro (2009). cem:
Coarsened exact matching in Stata. The Stata Journal, Volume 9 Number 4:
pp. 524-546
http://www.stata-journal.com/article.html?article=st0176
--
Sergio
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