Cluster Randomized Trials With Treatment Noncompliance

Booil Jo, Tihomir Asparouhov, Bengt O. Muthén, Nicholas S Ialongo, C. Hendricks Brown

Research output: Contribution to journalArticle

Abstract

Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be related not only to individual characteristics but also to the environment of clusters individuals belong to. Therefore, analyses ignoring the connection between compliance and clustering may not provide valid results. Although randomized field experiments often suffer from both noncompliance and clustering of the data, these features have been studied as separate rather than concurrent problems. On the basis of Monte Carlo simulations, this study demonstrated how clustering and noncompliance may affect statistical inferences and how these two complications can be accounted for simultaneously. In particular, the effect of the intervention on individuals who not only were assigned to active intervention but also abided by this intervention assignment (complier average causal effect) was the focus. For estimation of intervention effects considering noncompliance and data clustering, an ML-EM estimation method was employed.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalPsychological Methods
Volume13
Issue number1
DOIs
Publication statusPublished - Mar 2008

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Keywords

  • cluster randomized trial
  • compliance intraclass correlation
  • complier average causal effect
  • ML-EM estimation
  • treatment noncompliance

ASJC Scopus subject areas

  • Psychology(all)

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