Multiple imputation procedures for estimating causal effects with multiple treatments with application to the comparison of healthcare providers-Reference-Cited by-同舟云学术

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Multiple imputation procedures for estimating causal effects with multiple treatments with application to the comparison of healthcare providers

Published:2021-11-02 Issue:1 Volume:41 Page:208-226
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Silva Gabriella C.¹^ORCID,Gutman Roee¹

Affiliation:

1. Department of Biostatistics Brown University Providence Rhode Island USA

Funder

Agency for Healthcare Research and Quality

National Institute on Aging

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9231

Reference48 articles.

1. Estimating causal effects of treatments in randomized and nonrandomized studies.

2. Evaluating the econometric evaluations of training programs with experimental data;LaLonde R;Am Econ Rev,1986

3. DehejiaR WahbaS.Causal effects in non‐experimental studies: re‐evaluating the evaluation of training programs; 1998.10.3386/w6586

4. Testing treatment effects in unconfounded studies under model misspecification: Logistic regression, discretization, and their combination

5. Robust estimation of causal effects of binary treatments in unconfounded studies with dichotomous outcomes

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