Practical Guide to Cluster Randomised Trials in Health Services Research

Sandra Eldridge – Senior Lecturer, Medical Statistics, Queen Mary, University of London, UKDr Eldridge is well experienced in designing and analyzing high quality cluster randomized trials, having worked on ten such trials since the mid 1990s. An award-winning speaker on randomized trials, Dr Eldridge has given numerous presentations in many settings and conferences over the last seven years.

“There are several unique strengths to this book. In particular the authors are very experienced statisticians having worked for many years in the design and analysis of cluster randomized trials and have written excellent methodological articles many of which are cited in their book.”  (Journal of Biopharmaceutical Statistics, 2012)

• Preface xiii Notation xvTable of cases: Trials used as examples in more than one chapter in the book xviii1 Introduction 11.1 Introduction to randomised trials 21.2 Explanatory or pragmatic trials 21.3 How does a cluster randomised trial differ from other trials? 31.4 Between-cluster variability 91.5 Why carry out cluster randomised trials? 101.6 Quality of evidence from cluster randomised trials 131.7 Historical perspectives 161.8 Summary 18References 192 Recruitment and ethics 222.1 Selecting clusters and participants to enhance external validity 222.2 Ethics of cluster randomised trials 242.3 Selection and recruitment of participants to enhance internal validity 352.4 Retention of participants in the trial 412.5 Summary 41References 413 Designing interventions 443.1 Lack of effectiveness of interventions evaluated in cluster randomised trials 453.2 What is a complex intervention? 463.3 Phases in the development of a complex intervention 503.4 Identifying evidence for potential intervention effect (pre-clinical phase) 503.5 Understanding more about intervention components (modelling phase) 533.6 Developing the optimum intervention and study design (exploratory trial phase) 553.7 What is the intervention? 573.8 Summary 58References 584 Pilot and feasibility studies 604.1 What is a pilot study? 604.2 Reasons for conducting pilot and feasibility studies 634.3 Designing a pilot or feasibility study 694.4 Reporting and interpreting pilot studies 714.5 Summary 72References 735 Design 745.1 Parallel designs with only two arms 755.2 Cohort versus cross-sectional designs 855.3 Parallel designs with more than two arms 885.4 Crossover designs 925.5 Further design considerations 955.6 Summary 96References 966 Analysis 996.1 Data collection and management 996.2 Analysis – an introduction 1016.3 Analyses for two-arm, completely randomised, stratified or minimised designs 1046.4 Analyses for other designs 1246.5 Intention to treat and missing values 1296.6 Analysis planning 1316.7 Summary 132References 1337 Sample size calculations 1377.1 Factors affecting sample size for cluster randomised designs 1387.2 Calculating sample size using the intra-cluster correlation coeffi cient 1427.3 Sample size calculations for rates 1457.4 Restricted number of clusters 1467.5 Trials with a small number of clusters 1497.6 Variability in cluster size 1507.7 Comparison of different measures of between-cluster variability 1547.8 Matched and stratifi ed designs 1607.9 Sample size for other designs 1667.10 Summary 169References 1698 The intra-cluster correlation coeffi cient 1728.1 What is the ICC? 1738.2 Sources of ICC estimates 1758.3 Choosing the ICC for use in sample size calculations 1798.4 Calculating ICC values 1858.5 Uncertainty in ICCs 1928.6 Summary 193References 1939 Other topics 196Richard Grieve9.1 Systematic reviews 1979.2 Cost effectiveness analyses 2079.3 Process evaluation 2129.4 Monitoring 2139.5 Summary 215References 21510 Trial reporting 21810.1 Trial quality and reporting quality 21810.2 Steps to improve trial reporting in the early stages of the trial 22710.3 Reporting randomised trials in journal and conference abstracts 23010.4 Application of CONSORT statement to cluster randomised trials 23210.5 Summary 262References 263Index 267