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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Bibliographische Detailangaben

Veröffentlicht in:	American journal of epidemiology Jg. 188; H. 1; S. 250
Hauptverfasser:	Li, Fan, Thomas, Laine E
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.01.2019
Schlagworte:	Bias Causality Epidemiologic Methods Humans Models, Statistical Propensity Score
ISSN:	1476-6256, 1476-6256
Online-Zugang:	Weitere Angaben
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