Evidence map›Paper›PMID 27899073›Full record

ReviewBMC medical research methodology2016

Recommendations for the analysis of individually randomised controlled trials with clustering in one arm - a case of continuous outcomes.

Laura Flight, Annabel Allison, Munyaradzi Dimairo, Ellen Lee, Laura Mandefield, Stephen J Walters

Registry-linked trialOpen access · goldAbstract readReview
In one paragraph

Review in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06455397 (Implementing BEAM), which is not on this map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06455397 narecruitingnot on this mapstarted 2024, after this paper: background citation

Implementing BEAM: An mHealth Tool to Prevent Mental Health Problems and Improve Developmental Outcomes in Young Children

TypeinterventionalSponsorLeslie E. RoosRan2024 to 2027Enrolled400ConditionsDepression, Anxiety, Anger, Parenting, Stress, PsychologicalArmsThe Building Emotional Awareness and Mental Health (BEAM) Program
3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 71 citations in OpenAlex.

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  17. Camaraderie: Profession-Specific Facilitated Small Groups to Improve Well-Being in Health Care.Mayo Clinic proceedings. Innovations, quality & outcomes · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Laura FlightScHARR, University of Sheffield, 30 Regent Street, Sheffield, S1 4DA, UK.
Annabel AllisonMRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.
Munyaradzi DimairoScHARR, University of Sheffield, 30 Regent Street, Sheffield, S1 4DA, UK.
Ellen LeeScHARR, University of Sheffield, 30 Regent Street, Sheffield, S1 4DA, UK.
Laura MandefieldScHARR, University of Sheffield, 30 Regent Street, Sheffield, S1 4DA, UK.
Stephen J WaltersScHARR, University of Sheffield, 30 Regent Street, Sheffield, S1 4DA, UK. s.j.walters@sheffield.ac.uk.ORCID 0000-0001-9000-8126
University of Sheffield · GBMRC Biostatistics Unit · GB

Funding

Department of Health DRF-2012-05-182
6 · The paper itself

Abstract

backgroundIn an individually randomised controlled trial where the treatment is delivered by a health professional it seems likely that the effectiveness of the treatment, independent of any treatment effect, could depend on the skill, training or even enthusiasm of the health professional delivering it. This may then lead to a potential clustering of the outcomes for patients treated by the same health professional, but similar clustering may not occur in the control arm. Using four case studies, we aim to provide practical guidance and recommendations for the analysis of trials with some element of clustering in one arm.

methodsFive approaches to the analysis of outcomes from an individually randomised controlled trial with clustering in one arm are identified in the literature. Some of these methods are applied to four case studies of completed randomised controlled trials with clustering in one arm with sample sizes ranging from 56 to 539. Results are obtained using the statistical packages R and Stata and summarised using a forest plot.

resultsThe intra-cluster correlation coefficient (ICC) for each of the case studies was small (<0.05) indicating little dependence on the outcomes related to cluster allocations. All models fitted produced similar results, including the simplest approach of ignoring clustering for the case studies considered.

conclusionsA partially clustered approach, modelling the clustering in just one arm, most accurately represents the trial design and provides valid results. Modelling homogeneous variances between the clustered and unclustered arm is adequate in scenarios similar to the case studies considered. We recommend treating each participant in the unclustered arm as a single cluster. This approach is simple to implement in R and Stata and is recommended for the analysis of trials with clustering in one arm only. However, the case studies considered had small ICC values, limiting the generalisability of these results.

Indexed as

AlgorithmsModels, TheoreticalCluster AnalysisHumansOutcome Assessment, Health CareRandomized Controlled Trials as TopicReproducibility of ResultsResearch DesignSample SizeClusteringIndividually clustered randomised controlled trialsRandomised controlled trialStatistical modelsTherapist effects

Identifiers

PMID27899073
PMCPMC5129671
OpenAlexW2559536423

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.