Propensity-score matching in the cardiovascular surgery literature from 2004 to 2006: a systematic review and suggestions for improvement.

By Peter C. Austin. Journal of Thoracic and Cardiovascular Surgery, 2007

596 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Epidemiology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c98f7b350b340f2342989fde3ccea4fedcd24452

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In Cardiology and Cardiovascular Medicine

In Epidemiology

In Statistics and Probability

Citations in the corpus

The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments (2013, background): “Thus, we think that, while the log-rank test is frequently used for testing the equality of survival curves in propensity score matched samples [9, 10, 35], such an approach is inappropriate, because it requires that the samples be independent of one another [36, 37].”
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies (2011, background): “Prior Monte Carlo studies have compared the relative performance of the different propensity score methods for estimating risk differences, relative risks, and marginal and conditional odds ratios (Austin, 2007b, 2008c, 2010; Austin, Grootendorst, Normand, & Anderson, 2007).”
Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies (2010, unknown): “It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates.”
An introduction to propensity-score methods for reducing confounding in observational studies (2011, unknown): “Indeed, in the medical literature, a wide range of caliper widths have been used (Austin, 2007a, 2008b). Cochran and Rubin (1973) examined the reduction in bias due to a single normally distributed confounding variable by matching on this confounding variable using calipers whose widths were proport”
A comparison of 12 algorithms for matching on the propensity score (2013, background): “In the medical literature, the latter appears to be the most common matching method, although there is no consistency in the caliper width that is used [3, 4].”
Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples (2009, background): “’s proscription against the use of significance testing has been echoed elsewhere [7, 8].”