Propensity score matching method (PSM) is widely used in observational study to reduce selection bias. Observational study lacks randomization, hence, statistical inferences without bias adjustments usually include observed or unobserved effects of covariates. If a subject with specific characteristics has a higher chance to be selected for a specific treatment, the characteristics have a possible effect on statistical results. PSM is the method for controlling covariate imbalance that produces the selection bias. In this paper, we introduce the basic concepts of PSM and simplified methods of PSM process. However, PSM is a rapidly developing statistical area with many limitations and some disadvantages. These points are described in the concluding section to emphasize the importance of considering the various features of PSM in the study design.
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