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On Regression Adjustment for the Propensity Score

Statistics in Medicine, 2014
Propensity scores are widely adopted in observational research because they enable adjustment for high-dimensional confounders without requiring models for their association with the outcome of interest.
Rhian Daniel, Stijn Vansteelandt
exaly   +3 more sources

Covariate Adjustment and Propensity Score [PDF]

JAMA - Journal of the American Medical Association, 2016
Melissa M Garrido
exaly   +3 more sources

On Variance Estimate for Covariate Adjustment by Propensity Score Analysis [PDF]

Statistics in Medicine, 2016
Propensity score (PS) methods have been used extensively to adjust for confounding factors in the statistical analysis of observational data in comparative effectiveness research. There are four major PS-based adjustment approaches: PS matching, PS stratification, covariate adjustment by PS, and PS-based inverse probability weighting (IPW).
Patrick J Tighe, Jonathan Shuster, Haibo Zhou   +2 more
exaly   +4 more sources

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Goodness-of-Fit Diagnostics for the Propensity Score Model When Estimating Treatment Effects Using Covariate Adjustment With the Propensity Score

Pharmacoepidemiology and Drug Safety, 2008
Abstract The propensity score is defined to be a subject's probability of treatment selection, conditional on observed baseline covariates. Conditional on the propensity score, treated and untreated subjects have similar distributions of observed baseline covariates.
Peter Austin
exaly   +3 more sources

Confounding: Propensity score adjustment

Nutrition, 2006
In earlier columns [1–3], I highlighted how the determiation of the association between an exposure (e.g., vitamin supplementation) and a disease (e.g., coronary heart disase [CHD]) is not quite so straightforward as it might first ppear. In particular, confounding variables very often obcure the association of real scientific interest. For instance, n
openaire   +2 more sources

Propensity Score Adjustment Methods

2019
exaly   +2 more sources