{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Edwards T"],"funding":["foreign, commonwealth and development office","Joint award from UK Medical Research Council"],"pagination":["33-42"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12909608"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(1)"],"pubmed_abstract":["<h4>Background</h4>Individual non-compliance with an intervention in cluster randomised trials can occur and estimating an intervention effect according to intention-to-treat ignores non-compliance and underestimates efficacy. The effect of the intervention among compliers (the complier average causal effect) provides an unbiased estimate of efficacy but inference can be complex in cluster randomised trials.<h4>Methods</h4>We evaluated the performance of a pragmatic bootstrapping approach accounting for clustering to obtain a 95% confidence interval (CI) for a CACE for cluster randomised trials with monotonicity and one-sided non-compliance. We investigated a variety of scenarios for correlated cluster-level prevalence of a binary outcome and non-compliance (5%, 10%, 20%, 30%, 40%). Cluste"],"journal":["Clinical trials (London, England)"],"pubmed_title":["Practical inference for a complier average causal effect in cluster randomised trials with a binary outcome."],"pmcid":["PMC12909608"],"funding_grant_id":["MR/R010161/1"],"pubmed_authors":["Opondo C","Edwards T","Thompson J","Allen E"],"additional_accession":[]},"is_claimable":false,"name":"Practical inference for a complier average causal effect in cluster randomised trials with a binary outcome.","description":"<h4>Background</h4>Individual non-compliance with an intervention in cluster randomised trials can occur and estimating an intervention effect according to intention-to-treat ignores non-compliance and underestimates efficacy. The effect of the intervention among compliers (the complier average causal effect) provides an unbiased estimate of efficacy but inference can be complex in cluster randomised trials.<h4>Methods</h4>We evaluated the performance of a pragmatic bootstrapping approach accounting for clustering to obtain a 95% confidence interval (CI) for a CACE for cluster randomised trials with monotonicity and one-sided non-compliance. We investigated a variety of scenarios for correlated cluster-level prevalence of a binary outcome and non-compliance (5%, 10%, 20%, 30%, 40%). Cluste","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Feb","modification":"2026-07-16T04:59:20.718Z","creation":"2026-07-09T13:10:08.819Z"},"accession":"S-EPMC12909608","cross_references":{"pubmed":["41099213"],"doi":["10.1177/17407745251378407"]}}