Method

Causal inference methods

Statistical methods that estimate causal treatment effects from observational data by balancing confounders, including propensity score matching, inverse probability weighting, marginal structural models, and target trial emulation.

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Scholars using this

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MF
Mario Fl GaudinoStephen and Suzanne Weiss Professor in Cardiothoracic Surgery II
MF
Mario Fl GaudinoStephen and Suzanne Weiss Professor in Cardiothoracic Surgery II
AS
Art SedrakyanProfessor of Population Health Sciences
AS
Art SedrakyanProfessor of Population Health Sciences
LJ
Laith Jamal Abu-RaddadProfessor of Population Health Sciences
LJ
Laith Jamal Abu-RaddadProfessor of Population Health Sciences
LN
Leonard N GirardiChair of Cardiothoracic Surgery
LN
Leonard N GirardiChair of Cardiothoracic Surgery
BM
Beth McGintyChief, Health Policy and Economics
BM
Beth McGintyChief, Health Policy and Economics
BR
Bjorn RedforsProfessor of Research in Population Health Sciences
BR
Bjorn RedforsProfessor of Research in Population Health Sciences

Spotlight

Causal inference methods

BRBjorn Redfors

European heart journal. Cardiovascular pharmacotherapy · 2026

Causal inference methods

BRBjorn Redfors MFMario Fl Gaudino JZJudy Zhong

European heart journal. Quality of care & clinical outcomes · 2026

Causal inference methods

LJLouis J Aronne

Nature medicine · 2026

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Causal inference methods

Scholars using this

When Randomization Is Not Enough: Divergent Beta-Blocker Trials and the Illusion of Universal Causality.

Potential bias in efficacy estimates due to intercurrent treatment discontinuations.

Orforglipron for maintenance of body weight reduction: the double-blind, randomized phase 3b ATTAIN-MAINTAIN trial.