Bibliographic Information

Cluster randomised trials

Richard J. Hayes, Lawrence H. Moulton

(Interdisciplinary statistics)

CRC Press, c2009

Available at  / 5 libraries

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Note

"A Chapman & Hall book."

Includes bibliographical references (p. 303-307) and index

HTTP:URL=http://www.loc.gov/catdir/toc/ecip0826/2008035804.html Information=Table of contents only

Contents of Works

  • Variability between clusters
  • Choosing whether to randomise by cluster
  • Choice of clusters
  • Matching and stratification
  • Randomisation procedures
  • Sample size
  • Alternative study designs
  • Basic principles of analysis
  • Analysis based on cluster-level summaries
  • Regression analysis based on individual-level data
  • Analysis of trials with more complex designs
  • Ethical considerations
  • Data monitoring
  • Reporting and interpretation

Description and Table of Contents

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.

Table of Contents

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

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