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Updated: Jan 1, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Propensity weighting: how to minimise comparative bias in non-randomised studies?
Philip Moons1,2,3
1KU Leuven Department of Public Health and Primary Care, KU Leuven, Belgium.
Abstract:
Non-randomised study designs are frequently used by researchers in cardiovascular nursing and allied professions. Baseline differences between the groups to be compared may introduce bias in the results. Methods for causal inference address this issue. One such method is propensity weighting, in which two or more treatments/exposure groups are weighted to make the groups as comparable as possible. As such, it mimics a randomised controlled trial design. In this article, the Twang package is presented for propensity weighting, and its use is exemplified in a study on smoking and cannabis consumption in adults with congenital heart disease.
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