Cluster Randomised Trials

London School of Hygiene & Tropical Medicine, London, UK Johns Hopkins Bloomberg School of Public Health, Baltimore, University of Kent, UK University of Copenhagen, Denmark Utrecht University, The Netherlands University of California, Berkeley, USA

BASIC CONCEPTS


Introduction


Randomised Trials


Variability between Clusters


Introduction


The Implications of between-Cluster Variability: Some Examples


Measures of between-Cluster Variability


The Design Effect


Sources of within-Cluster Correlation





Choosing whether to Randomise by Cluster


Introduction


Rationale for Cluster Randomisation


Using Cluster Randomisation to Capture Indirect Effects of Intervention


Disadvantages and Limitations of Cluster Randomisation





DESIGN ISSUES


Choice of Clusters


Introduction


Types of Cluster


Size of Clusters


Strategies to Reduce Contamination


Levels of Randomisation, Intervention, Data Collection, and Inference





Matching and Stratification


Introduction


Rationale for Matching


Disadvantages of Matching


Stratification as an Alternative to Matching


Choice of Matching Variables


Choosing whether to Match or Stratify





Randomisation Procedures


Introduction


Restricted Randomisation


Some Practical Aspects of Randomisation





Sample Size


Introduction


Sample Size for Unmatched Trials


Sample Size for Matched and Stratified Trials


Estimating the between-Cluster Coefficient of Variation


Choice of Sample Size in Each Cluster


Further Issues in Sample Size Calculation





Alternative Study Designs


Introduction


Design Choices for Treatment Arms


Design Choices for Impact Evaluation





ANALYTICAL METHODS


Basic Principles of Analysis


Introduction


Experimental and Observational Units


Parameters of Interest


Approaches to Analysis


Baseline Analysis





Analysis Based on Cluster-Level Summaries


Introduction


Point Estimates of Intervention Effects


Statistical Inference Based on the t Distribution


Statistical Inference Based on a Quasilikelihood Approach


Adjusting for Covariates


Nonparametric Methods


Analysing for Effect Modification





Regression Analysis Based on Individual-Level Data


Introduction


Random Effects Models


Generalised Estimating Equations


Choice of Analytical Method


Analysing for Effect Modification


More Complex Analyses


Analysis of Trials with More Complex Designs


Introduction


Analysis of Pair-Matched Trials


Analysis of Stratified Trials


Analysis of Other Study Designs





MISCELLANEOUS TOPICS


Ethical Considerations


Introduction


General Principles


Ethical Issues in Group Allocation


Informed Consent in Cluster Randomised Trials


Other Ethical Issues


Conclusion


Data Monitoring


Introduction


Data Monitoring Committees


Interim Analyses


Reporting and Interpretation


Introduction


Reporting of Cluster Randomised Trials


Interpretation and Generalisability





References


Index