Cluster Randomised Trials

Richard J. Hayes, Lawrence H. Moulton

January 12, 2009 by Chapman and Hall/CRC
Reference - 338 Pages - 22 B/W Illustrations
ISBN 9781584888161 - CAT# C8164
Series: Chapman & Hall/CRC Biostatistics Series

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Features

  • Presents simple methods that are easy to apply with readily available statistical software and that perform well under the conditions experienced in most CRTs
  • Provides substantial material on study design options
  • Includes a variety of practical examples from both developing and industrialized countries, with many of the examples based on the authors’ own research
  • Illustrates the application of analytical methods through several data sets from actual trials
  • Shows how data can be analyzed using Stata

Summary

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.