Estimating the Complier Average Causal Effect via a latent class approach using gsem

Patricio Troncoso, Ana Morales-Gómez

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
186 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)404-415
Number of pages12
JournalThe Stata Journal
Volume22
Issue number2
DOIs
Publication statusPublished - 30 Jun 2022

Keywords

  • adherence
  • compliance
  • complier average causal effect
  • gsem
  • latent class modeling
  • mixture modeling
  • randomized control trial
  • st0677

ASJC Scopus subject areas

  • Mathematics (miscellaneous)

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