Cluster randomized trials with treatment noncompliance.
Open accessAbstract
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.
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CACE modeling is one analytic method for incomplete adoption.
“One analytical approach to accounting for incomplete adoption is to use Complier Average Causal Effect (commonly known as CACE) modeling (3, 9, 60).”
From An Overview of Research and Evaluation Designs for Dissemination and Implementation (2017) · cites this paper as [60]
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- Authors
- Jo, B., Asparouhov, T., Muthén, B. O., Ialongo, N. S., & Brown, C. H.
- Affiliations
- Stanford University (US)
- Muthén & Muthén (United States) (US)
- University of California, Los Angeles (US)
- Johns Hopkins University (US)
- University of South Florida (US)
- Venue
- Psychological Methods
- Published
- 2008
- Volume
- 13
- Issue
- 1
- Pages
- 1-18
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- PMC
- PMC2917590
- OpenAlex
- W1998990236
- Cited by
- 83
- References
- 61
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 11 · 2019: 6 · 2018: 8 · 2017: 5 · 2016: 7 · 2015: 2 · 2014: 3 · 2013: 4 · 2012: 2
- FWCI
- 5.98
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (MH066319; MH066247; MH40859)
- National Institute on Drug Abuse (DA11796)
- National Institute on Alcohol Abuse and Alcoholism (AA00230)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- treatment non-adherence, clustering, complier average causal effect, statistical inference, field experiments, Monte Carlo simulation
- MeSH terms
- Mental Disorders, Humans, Monte Carlo Method, Patient Compliance, Cluster Analysis, Randomized Controlled Trials as Topic
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