Statistics Applied to Clinical Studies pp 329-336 | Cite as

# Propensity Score Matching

## Abstract

Propensity-scores and propensity-score-matching can be used respectively for adjusting covariates in a multiple regression analysis and for stratification/matching of asymmetric observational clinical data, and have recently been emphasized by Dr. D’Agostino in an invited paper in Circulation as a promising additional tool for analyzing such data (D’Agostino 2007). It was first described by Rosenbaum and Rubin in 1985 (Rosenbaum and Rubin 1985), as a method for adjusting confounding variables, otherwise called covariates, alternative to the usual subclassification and regression methods. In the pas few years its application has been extended to so-called propensity-score-matching, a method able to transform asymmetric into symmetric data that can be further analyzed like randomized controlled trials. Due to the increase of costs for randomized trials, more and more clinical investigators turn to observational studies as a method of research. The current chapter was written to familiarize the readership of this book with these relatively novel methods.

## Keywords

Propensity Score Treatment Comparison Multiple Risk Factor Cardiovascular Research Real Clinical Practice## References

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- Love TE (2003) Propensity scores: what do they do, how should I use them and why should I care? www.chrp.org/love/ASACleveland, Accessed 15 Dec 2011
- Rosenbaum PR, Rubin DB (1985) Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat 39:33–38Google Scholar