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Why the Propensity for Propensity Scores?*
Critical Care Medicine, 2015The propensity score (PS) was introduced by Rosenbaum and Rubin in 1983 as a way to eliminate confounding by indication (1) from observed covariates in observational studies of causal effects (2). The PS is the estimated probability that an individual would receive treatment (or be in the exposure ...
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Invited Commentary: Propensity Scores
American Journal of Epidemiology, 1999The propensity score is the conditional probability of exposure to a treatment given observed covariates. In a cohort study, matching or stratifying treated and control subjects on a single variable, the propensity score, tends to balance all of the observed covariates; however, unlike random assignment of treatments, the propensity score may not also ...
M M, Joffe, P R, Rosenbaum
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Evaluation Review, 2005
Propensity score analysis is a relatively recent statistical innovation that is useful in the analysis of data from quasi-experiments. The goal of propensity score analysis is to balance two non-equivalent groups on observed covariates to get more accurate estimates of the effects of a treatment on which the two groups differ.
Jason K, Luellen +2 more
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Propensity score analysis is a relatively recent statistical innovation that is useful in the analysis of data from quasi-experiments. The goal of propensity score analysis is to balance two non-equivalent groups on observed covariates to get more accurate estimates of the effects of a treatment on which the two groups differ.
Jason K, Luellen +2 more
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Propensity-Score Matching: The "Devil is in the Details" Where More May Be Hidden Than You Know.
American Journal of Medicine, 2020Propensity-score matching has been used with increasing frequency in the analyses of non-prespecified subgroups of randomized clinical trials as well as in retrospective analyses of clinical trial data sets, registries, observational studies, electronic ...
J. Reiffel
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To use or not to use propensity score matching?
Pharmaceutical statistics, 2020Propensity score matching (PSM) has been widely used to reduce confounding biases in observational studies. Its properties for statistical inference have also been investigated and well documented.
Jixian Wang
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Confounding: Propensity score adjustment
Nutrition, 2006In 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
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Advances in Developing Human Resources, 2014
The Problem Flexible work arrangements (FWAs) have long been heralded as antecedent to numerous positive organizational attitudes and outcomes. However, results on FWAs benefits are mixed which may be due to differences in employee characteristics. Not all individuals may desire such arrangements.
Lane, Forrest C., Gibbs, SherRhonda
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The Problem Flexible work arrangements (FWAs) have long been heralded as antecedent to numerous positive organizational attitudes and outcomes. However, results on FWAs benefits are mixed which may be due to differences in employee characteristics. Not all individuals may desire such arrangements.
Lane, Forrest C., Gibbs, SherRhonda
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2011
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 ...
Ton J. Cleophas, Aeilko H. Zwinderman
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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 ...
Ton J. Cleophas, Aeilko H. Zwinderman
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Understanding propensity scores
International Journal of Evidence-Based Healthcare, 2017Ritin, Fernandez, Catalin, Tufanaru
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