Addressing Extreme Propensity Scores via the Overlap Weights

The popular inverse probability weighting method in causal inference is often hampered by extreme propensity scores, resulting in biased estimates and excessive variance. A common remedy is to trim patients with extreme scores (i.e., remove them from the weighted analysis). However, such methods are...

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Bibliographic Details

Published in:	American journal of epidemiology Vol. 188; no. 1; p. 250
Main Authors:	Li, Fan, Thomas, Laine E
Format:	Journal Article
Language:	English
Published:	United States 01.01.2019
Subjects:	Bias Causality Epidemiologic Methods Humans Models, Statistical Propensity Score
ISSN:	1476-6256, 1476-6256
Online Access:	Get more information
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