Borrowing from supplemental sources to estimate causal effects from a primary data source-Reference-Cited by-同舟云学术

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Borrowing from supplemental sources to estimate causal effects from a primary data source

Published:2021-06-22 Issue:24 Volume:40 Page:5115-5130
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Boatman Jeffrey A.¹^ORCID,Vock David M.¹,Koopmeiners Joseph S.¹^ORCID

Affiliation:

1. Division of Biostatistics, School of Public Health University of Minnesota Minneapolis Minnesota USA

Funder

National Cancer Institute

National Institute on Drug Abuse

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9114

Reference27 articles.

1. Estimations and predictors of non-compliance in switchers to reduced nicotine content cigarettes

2. Randomized Trial of Low-Nicotine Cigarettes and Transdermal Nicotine

3. Randomized Trial of Reduced-Nicotine Standards for Cigarettes

4. Effect of Immediate vs Gradual Reduction in Nicotine Content of Cigarettes on Biomarkers of Smoke Exposure

5. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)

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1. Propensity score weighted multi‐source exchangeability models for incorporating external control data in randomized clinical trials;Statistics in Medicine;2024-06-24

2. A Bayesian platform trial design with hybrid control based on multisource exchangeability modelling;Statistics in Medicine;2024-04-09

3. Semi-supervised mixture multi-source exchangeability model for leveraging real-world data in clinical trials;Biostatistics;2023-09-11

4. A Guide to Selecting Flexible Survival Models to Inform Economic Evaluations of Cancer Immunotherapies;Value in Health;2023-02

5. Hierarchical Bayesian bootstrap for heterogeneous treatment effect estimation;The International Journal of Biostatistics;2022-12-30

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