A compound representation of the multiple treatment propensity score with applications to marginal structural modeling

• Published in: Epidemiologic methods Vol. 13; no. 2
• Main Authors: Stein, David, D’Arinzo, Lauren, Gaspar, Fraser, Oliver, Max, Fitzgerald, Kristin, Lu, Di, Piantadosi, Steven, Amin, Alpesh, Webb, Brandon
• Format: Journal Article
• Language: English
• Published: Berlin De Gruyter 06.11.2024; Walter de Gruyter GmbH
• Subjects: Bias; Clinical trials; Coronaviruses; COVID-19; Estimates; marginal structural models; multiple treatment propensity score; Observational studies; Pandemics; Regression analysis; Severe acute respiratory syndrome
• ISSN: 2161-962X; 2194-9263; 2161-962X
• DOI: 10.1515/em-2023-0005

Methods of causal inference are used to estimate treatment effectiveness for non-randomized study designs. The propensity score (i.e., the probability that a subject receives the study treatment conditioned on a set of variables related to treatment and/or outcome) is often used with matching or sam...