2011 ArePropensityScoresReallySuperi

• (Biondi-Zoccai et al., 2011) ⇒ Giuseppe Biondi-Zoccai, Enrico Romagnoli, Pierfrancesco Agostoni, Davide Capodanno, Davide Castagno, Fabrizio D'Ascenzo, Giuseppe Sangiorgi, and Maria Grazia Modena. (2011). “Are Propensity Scores Really Superior to Standard Multivariable Analysis?.” In: Contemporary Clinical Trials, 32(5). doi:10.1016/j.cct.2011.05.006

Subject Headings: Propensity Score; Propensity Score Matching

Cited By

• http://scholar.google.com/scholar?q=%22Are+propensity+scores+really+superior+to+standard+multivariable+analysis%3F%22+2011

Quotes

Author Keywords

• Bias; Cox proportional hazard analysis; Logistic regression; Multivariable analysis; Propensity score

Abstract

Clinicians often face difficult decisions despite the lack of evidence from randomized trials. Thus, clinical evidence is often shaped by non-randomized studies exploiting multivariable approaches to limit the extent of confounding. Since their introduction, propensity scores have been used more and more frequently to estimate relevant clinical effects adjusting for established confounders, especially in small datasets. However, debate persists on their real usefulness in comparison to standard multivariable approaches such as logistic regression and Cox proportional hazard analysis. This holds even truer in light of key quantitative developments such as bootstrap and Bayesian methods. This qualitative review aims to provide a concise and practical guide to choose between propensity scores and standard multivariable analysis, emphasizing strengths and weaknesses of both approaches.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 ArePropensityScoresReallySuperi	Giuseppe Biondi-Zoccai Enrico Romagnoli Pierfrancesco Agostoni Davide Capodanno Davide Castagno Fabrizio D'Ascenzo Giuseppe Sangiorgi Maria Grazia Modena			Are Propensity Scores Really Superior to Standard Multivariable Analysis?				10.1016/j.cct.2011.05.006		2011