Evidence map›Paper›PMID 22627076›Full record

ArticleContemporary clinical trials2012

Comparison of methods for estimating the intraclass correlation coefficient for binary responses in cancer prevention cluster randomized trials.

Sheng Wu, Catherine M Crespi, Weng Kee Wong

2 registry-linked trialsAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Contemporary clinical trials, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 127 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
127citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT02783950 nacompletednot on this mapstarted 2017, after this paper: background citation

Genomics in Michigan Impacting Observation or Radiation (G-MINOR)

TypeinterventionalSponsorUniversity of Michigan Rogel Cancer CenterRan2017 to 2024Enrolled356ConditionsProstate CancerArmsDecipher Prostate Cancer Classifier
NCT04588376 nacompletednot on this mapstarted 2015, after this paper: background citation

Improving Antibiotic Prescribing for Pediatric Acute Respiratory Tract Infections: Cluster Randomized Trial to Evaluate Individual Clinician Compared With Clinic-level Feedback

TypeinterventionalSponsorHerb CleggRan2015 to 2018Enrolled39ConditionsUpper Respiratory Infection, Acute Bacterial Sinusitis, Acute Otitis MediaArmsPeer comparison feedback monthly
3 · Its place in the literature

Who cites it

127 citing papers in PubMed, 1 synthesis or guideline pooled it.

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67 more citing papers are in PubMed but not listed here.

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

3 authors.

Sheng WuDepartment of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Center for the Health Sciences, Los Angeles, CA 90095-1772, USA. shengwu@ucla.edu
Catherine M Crespi
Weng Kee Wong

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
Promoting Hepatitis B Screening for Vietnamese American AdultsP01CA109091 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MAXWELL, ANNETTE · 2006 to 2010
$7.8M
New Methods for the Design of Cancer Studies with Clustered Binary OutcomesR03CA137827 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CRESPI, CATHERINE · 2009 to 2010
$154k
NCI NIH HHS CA109091NCI NIH HHS CA137827NCI NIH HHS CA16042NCI NIH HHS P01 CA109091NCI NIH HHS P30 CA016042NCI NIH HHS R03 CA137827
6 · The paper itself

Abstract

The intraclass correlation coefficient (ICC) is a fundamental parameter of interest in cluster randomized trials as it can greatly affect statistical power. We compare common methods of estimating the ICC in cluster randomized trials with binary outcomes, with a specific focus on their application to community-based cancer prevention trials with primary outcome of self-reported cancer screening. Using three real data sets from cancer screening intervention trials with different numbers and types of clusters and cluster sizes, we obtained point estimates and 95% confidence intervals for the ICC using five methods: the analysis of variance estimator, the Fleiss-Cuzick estimator, the Pearson estimator, an estimator based on generalized estimating equations and an estimator from a random intercept logistic regression model. We compared estimates of the ICC for the overall sample and by study condition. Our results show that ICC estimates from different methods can be quite different, although confidence intervals generally overlap. The ICC varied substantially by study condition in two studies, suggesting that the common practice of assuming a common ICC across all clusters in the trial is questionable. A simulation study confirmed pitfalls of erroneously assuming a common ICC. Investigators should consider using sample size and analysis methods that allow the ICC to vary by study condition.

Indexed as

Data Interpretation, StatisticalBreast NeoplasmsColonic NeoplasmsEarly Detection of CancerHumansModels, StatisticalNeoplasmsRandomized Controlled Trials as TopicResearch DesignStatistics as Topic

Identifiers

PMID22627076
PMCPMC3426610

What OpenQuestion holds

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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.