Troncoso, P. and Morales-Gómez, A. (2022) Estimating the complier average causal effect via a latent class approach using gsem. The Stata Journal: Promoting communications on statistics and Stata, 22 (2). pp. 404-415. ISSN 1536-867X
Abstract
In randomized controlled trials, intention-to-treat analysis is customarily used to estimate the effect of the trial. However, in the presence of noncompliance, this can often lead to biased estimates because intention-to-treat analysis completely ignores varying levels of actual treatment received. This is a known issue that can be overcome by adopting the complier average causal effect approach, which estimates the effect the trial had on the individuals who complied with the protocol. When compliance is unobserved in the control group, the complier average causal effect estimate can be obtained via a latent class specification using the gsem command.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © StataCorp LLC 2022. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | st0677; gsem; complier average causal effect; randomized control trial; compliance; adherence; latent class modeling; mixture modeling |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Law (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 Feb 2023 15:02 |
Last Modified: | 10 Feb 2023 15:02 |
Status: | Published |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/1536867x221106416 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:196283 |