Abstract
The authors presents a propensity score matching (PSM) technique - an effective method to control the effect of confounding factors in observational studies. PSM has been shown to be as efficient as linear regression analysis, but can be performed using smaller samples. This article presents the basic principles of PSM and its practical application using STATA 13 software for the studies with continuous dependent variable.