Using inverse probability-weighted estimators in comparative effectiveness analyses with observational databases.
Inverse probability-weighted estimation is a powerful tool for use with observational data. In this article, we describe how this propensity score-based method can be used to compare the effectiveness of 2 or more treatments. First, we discuss the inherent problems in using observational data to assess comparative effectiveness. Next, we provide a conceptual explanation of inverse probability-weighted estimation and point readers to sources that address the method in more formal, technical terms. Finally, we offer detailed guidance about how to implement the estimators in comparative effectiveness analyses.
Curtis
Lesley H
LH
Duke Clinical Research Institute, and Departments of Medicine, Duke University School of Medicine, Durham, North Carolina, USA. lesley.curtis@duke.edu
Hammill
Bradley G
BG
Eisenstein
Eric L
EL
Kramer
Judith M
JM
Anstrom
Kevin J
KJ
D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000706:statistics & numerical data; D004341:Drug Evaluation / Q000706:statistics & numerical data*; D015981:Epidemiologic Factors; D006801:Humans; D053208:Kaplan-Meier Estimate; D015233:Models, Statistical; D019370:Observation; D011336:Probability; D012044:Regression Analysis