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基本説明
Discusses the design, conduct, and analysis of health trials that randomise groups of individuals to different treatments. Explores the advantages of cluster randomization, with special attention given to evaluating the effects of interventions against infectious diseases.
Full Description
Cluster Randomised Trials discusses the design, conduct, and analysis of health trials that randomise groups of individuals to different treatments. It explores the advantages of cluster randomization, with special attention given to evaluating the effects of interventions against infectious diseases.Avoiding unnecessary mathematical detail, the book covers basic concepts underlying the use of cluster randomisation, such as direct, indirect, and total effects. The authors also present an array of design issues in cluster randomised trials (CRTs), including strategies for minimizing contamination effects, the use of stratification and restricted randomisation to improve balance between treatment arms, special methods for sample size calculation, and alternatives to the simplest two-arm CRT. After covering analytical methods for CRTs, such as regression methods, the authors examine ethical issues, trial monitoring, interim analyses, reporting, and interpretation.Although the book mainly focuses on medical and public health applications, it shows that the rigorous evidence of intervention effects provided by CRTs has the potential to inform public policy in a wide range of other areas. The book encourages readers to apply the methods to their own trials, reproduce the analyses presented, and explore alternative approaches.
Contents
BASIC CONCEPTSIntroduction Randomised TrialsVariability between Clusters Introduction The Implications of between-Cluster Variability: Some Examples Measures of between-Cluster VariabilityThe Design EffectSources of within-Cluster CorrelationChoosing whether to Randomise by Cluster Introduction Rationale for Cluster RandomisationUsing Cluster Randomisation to Capture Indirect Effects of InterventionDisadvantages and Limitations of Cluster RandomisationDESIGN ISSUESChoice of Clusters Introduction Types of ClusterSize of ClustersStrategies to Reduce ContaminationLevels of Randomisation, Intervention, Data Collection, and InferenceMatching and Stratification Introduction Rationale for MatchingDisadvantages of MatchingStratification as an Alternative to Matching Choice of Matching VariablesChoosing whether to Match or StratifyRandomisation Procedures Introduction Restricted RandomisationSome Practical Aspects of RandomisationSample Size Introduction Sample Size for Unmatched TrialsSample Size for Matched and Stratified TrialsEstimating the between-Cluster Coefficient of VariationChoice of Sample Size in Each Cluster Further Issues in Sample Size CalculationAlternative Study DesignsIntroduction Design Choices for Treatment ArmsDesign Choices for Impact EvaluationANALYTICAL METHODSBasic Principles of Analysis Introduction Experimental and Observational Units Parameters of InterestApproaches to Analysis Baseline AnalysisAnalysis Based on Cluster-Level Summaries Introduction Point Estimates of Intervention EffectsStatistical Inference Based on the t DistributionStatistical Inference Based on a Quasilikelihood Approach Adjusting for CovariatesNonparametric MethodsAnalysing for Effect ModificationRegression Analysis Based on Individual-Level Data Introduction Random Effects ModelsGeneralised Estimating Equations Choice of Analytical Method Analysing for Effect Modification More Complex AnalysesAnalysis of Trials with More Complex Designs Introduction Analysis of Pair-Matched Trials Analysis of Stratified Trials Analysis of Other Study DesignsMISCELLANEOUS TOPICSEthical Considerations Introduction General PrinciplesEthical Issues in Group Allocation Informed Consent in Cluster Randomised TrialsOther Ethical IssuesConclusionData Monitoring Introduction Data Monitoring CommitteesInterim AnalysesReporting and Interpretation Introduction Reporting of Cluster Randomised TrialsInterpretation and GeneralisabilityReferencesIndex
