Estimating the complier average causal effect via a latent class approach using gsem

Troncoso, P. and Morales-Gómez, A. (2022) Estimating the complier average causal effect via a latent class approach using gsem. Stata Journal, 22(2), pp. 404-415. (doi: 10.1177/1536867X221106416)

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.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Troncoso, Dr Patricio
• Authors: Troncoso, P., and Morales-Gómez, A.
• Subjects: H Social Sciences > H Social Sciences (General); H Social Sciences > HA Statistics; Q Science > QA Mathematics > QA76 Computer software
• College/School: College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Journal Name: Stata Journal
• Publisher: SAGE
• ISSN: 1536-867X
• ISSN (Online): 1536-8734
• Published Online: 30 June 2022
• Copyright Holders: Copyright © 2022 StataCorpLLC
• First Published: First published in Stata Journal 22(2):404-415
• Publisher Policy: Reproduced under a Creative Commons licence