Evidence map›Paper›PMID 16109162›Full record

ArticleBMC medical research methodology2005

A priori postulated and real power in cluster randomized trials: mind the gap.

Lydia Guittet, Bruno Giraudeau, Philippe Ravaud

Abstract readComparative Study
In one paragraph

Article in BMC medical research methodology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Cluster-Randomized Studies.Deutsches Arzteblatt international · 2018
    Review
  6. How to design efficient cluster randomised trials.BMJ (Clinical research ed.) · 2017
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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.

Lydia GuittetDépartement d'Epidémiologie, Biostatistique et Recherche Clinique, Groupe Hospitalier Bichat-Claude Bernard (AP-HP) - Université Paris 7, Paris, France. lguittet@free.fr
Bruno Giraudeau
Philippe Ravaud

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCluster randomization design is increasingly used for the evaluation of health-care, screening or educational interventions. The intraclass correlation coefficient (ICC) defines the clustering effect and be specified during planning. The aim of this work is to study the influence of the ICC on power in cluster randomized trials.

methodsPower contour graphs were drawn to illustrate the loss in power induced by an underestimation of the ICC when planning trials. We also derived the maximum achievable power given a specified ICC.

resultsThe magnitude of the ICC can have a major impact on power, and with low numbers of clusters, 80% power may not be achievable.

conclusionUnderestimating the ICC during planning cluster randomized trials can lead to a seriously underpowered trial. Publication of a priori postulated and a posteriori estimated ICCs is necessary for a more objective reading: negative trial results may be the consequence of a loss of power due to a mis-specification of the ICC.

Indexed as

Cluster AnalysisData Interpretation, StatisticalConfidence IntervalsDecision TheoryGeographyHumansRandomized Controlled Trials as TopicResearch Design

Identifiers

PMID16109162
PMCPMC1190183

What OpenQuestion holds

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Registered trials

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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.