Effect of imbalance and intracluster correlation coefficient in cluster randomization trials with binary outcomes when the available number of clusters is fixed in advance

Abstract In some cluster randomization trials, the number of clusters cannot exceed a specified maximum value due to cost constraints or other practical reasons. Donner and Klar [Donner A, and Klar N. Design and analysis of cluster randomization trials in health research. Oxford University Press 200...

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Veröffentlicht in:Contemporary clinical trials 2009-07, Vol.30 (4), p.317-320
Hauptverfasser: Ahn, Chul, Hu, Fan, Skinner, Celette Sugg, Ahn, Daniel
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Hu, Fan
Skinner, Celette Sugg
Ahn, Daniel
description Abstract In some cluster randomization trials, the number of clusters cannot exceed a specified maximum value due to cost constraints or other practical reasons. Donner and Klar [Donner A, and Klar N. Design and analysis of cluster randomization trials in health research. Oxford University Press 2000] provided the sample size formula for the number of subjects required per cluster when the number of clusters cannot exceed a specified maximum value. The sample size formula of Donner and Klar assumes that the number of subjects is the same in each cluster. In practical situations, the number of subjects may be different among clusters. We conducted simulation studies to investigate the effect of the cluster size variability ( κ ) and the intracluster correlation coefficient ( ρ ) on the power of the study in which the number of available clusters is fixed in advance. For the balanced case ( κ = 1.0), i.e. , equal cluster size among clusters, the sample size formula yielded empirical powers close to the nominal level even when the number of available clusters per group ( k⁎ ) is as small as 10. The sample size formula yielded empirical powers close to the nominal level when the number of available clusters per group ( k⁎ ) is at least 20 and the imbalance parameter ( κ ) is at least 0.8. Empirical powers were close to the nominal level when ( ρ ≤ 0.02, κ ≥ 0.8, and k⁎ = 10) or ( ρ ≤ 0.02, κ = 0.8, and k⁎ = 20).
doi_str_mv 10.1016/j.cct.2009.03.007
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Donner and Klar [Donner A, and Klar N. Design and analysis of cluster randomization trials in health research. Oxford University Press 2000] provided the sample size formula for the number of subjects required per cluster when the number of clusters cannot exceed a specified maximum value. The sample size formula of Donner and Klar assumes that the number of subjects is the same in each cluster. In practical situations, the number of subjects may be different among clusters. We conducted simulation studies to investigate the effect of the cluster size variability ( κ ) and the intracluster correlation coefficient ( ρ ) on the power of the study in which the number of available clusters is fixed in advance. For the balanced case ( κ = 1.0), i.e. , equal cluster size among clusters, the sample size formula yielded empirical powers close to the nominal level even when the number of available clusters per group ( k⁎ ) is as small as 10. The sample size formula yielded empirical powers close to the nominal level when the number of available clusters per group ( k⁎ ) is at least 20 and the imbalance parameter ( κ ) is at least 0.8. Empirical powers were close to the nominal level when ( ρ ≤ 0.02, κ ≥ 0.8, and k⁎ = 10) or ( ρ ≤ 0.02, κ = 0.8, and k⁎ = 20).</description><identifier>ISSN: 1551-7144</identifier><identifier>EISSN: 1559-2030</identifier><identifier>DOI: 10.1016/j.cct.2009.03.007</identifier><identifier>PMID: 19348965</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>Binary outcomes ; Biological and medical sciences ; Cardiovascular ; Clinical trial. 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Donner and Klar [Donner A, and Klar N. Design and analysis of cluster randomization trials in health research. Oxford University Press 2000] provided the sample size formula for the number of subjects required per cluster when the number of clusters cannot exceed a specified maximum value. The sample size formula of Donner and Klar assumes that the number of subjects is the same in each cluster. In practical situations, the number of subjects may be different among clusters. We conducted simulation studies to investigate the effect of the cluster size variability ( κ ) and the intracluster correlation coefficient ( ρ ) on the power of the study in which the number of available clusters is fixed in advance. For the balanced case ( κ = 1.0), i.e. , equal cluster size among clusters, the sample size formula yielded empirical powers close to the nominal level even when the number of available clusters per group ( k⁎ ) is as small as 10. The sample size formula yielded empirical powers close to the nominal level when the number of available clusters per group ( k⁎ ) is at least 20 and the imbalance parameter ( κ ) is at least 0.8. Empirical powers were close to the nominal level when ( ρ ≤ 0.02, κ ≥ 0.8, and k⁎ = 10) or ( ρ ≤ 0.02, κ = 0.8, and k⁎ = 20).</description><subject>Binary outcomes</subject><subject>Biological and medical sciences</subject><subject>Cardiovascular</subject><subject>Clinical trial. Drug monitoring</subject><subject>Cluster Analysis</subject><subject>Computerized, statistical medical data processing and models in biomedicine</subject><subject>Data Interpretation, Statistical</subject><subject>Epidemiology</subject><subject>General aspects</subject><subject>General pharmacology</subject><subject>Hematology, Oncology and Palliative Medicine</subject><subject>Humans</subject><subject>Intracluster correlation</subject><subject>Medical sciences</subject><subject>Medical statistics</subject><subject>Methodology</subject><subject>Models, Statistical</subject><subject>Pharmacology. Drug treatments</subject><subject>Public health. Hygiene</subject><subject>Public health. 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The sample size formula yielded empirical powers close to the nominal level when the number of available clusters per group ( k⁎ ) is at least 20 and the imbalance parameter ( κ ) is at least 0.8. Empirical powers were close to the nominal level when ( ρ ≤ 0.02, κ ≥ 0.8, and k⁎ = 10) or ( ρ ≤ 0.02, κ = 0.8, and k⁎ = 20).</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>19348965</pmid><doi>10.1016/j.cct.2009.03.007</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record>
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subjects Binary outcomes
Biological and medical sciences
Cardiovascular
Clinical trial. Drug monitoring
Cluster Analysis
Computerized, statistical medical data processing and models in biomedicine
Data Interpretation, Statistical
Epidemiology
General aspects
General pharmacology
Hematology, Oncology and Palliative Medicine
Humans
Intracluster correlation
Medical sciences
Medical statistics
Methodology
Models, Statistical
Pharmacology. Drug treatments
Public health. Hygiene
Public health. Hygiene-occupational medicine
Randomized Controlled Trials as Topic - methods
sample size
Varying cluster size
title Effect of imbalance and intracluster correlation coefficient in cluster randomization trials with binary outcomes when the available number of clusters is fixed in advance
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