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Design and Analysis of Cluster Randomization Trials in Health Research

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Wednesday, March 12, 2014

Design and Analysis of Cluster Randomization Trials in Health Research [Hardcover]

Author: Allan Donner | Language: English | ISBN: 0470711000 | Format: PDF, EPUB

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Design and Analysis of Cluster Randomization Trials in Health Research
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A cluster randomization trial is one in which intact social units, or clusters of individuals, are randomized to different intervention groups. Trials randomizing clusters have become particularly widespread in the evaluation of non-therapeutic interventions, including lifestyle modification, educational programmes and innovations in the provision of health care. The increasing popularity of this design among health researchers over the past two decades has led to an extensive body of methodology on the subject. This is the first book to present a systematic and united treatment of this topic; it contains distinctive chapters on the history of cluster randomized trials, ethical issues and reporting guidelines.
Download latest books on mediafire and other links compilation Design and Analysis of Cluster Randomization Trials in Health Research [Hardcover]
  • Hardcover: 194 pages
  • Publisher: Wiley; 1 edition (May 17, 2010)
  • Language: English
  • ISBN-10: 0470711000
  • ISBN-13: 978-0470711002
  • Product Dimensions: 6.3 x 9.1 x 0.4 inches
  • Shipping Weight: 15.2 ounces (View shipping rates and policies)
  • Amazon Best Sellers Rank: #1,242,272 in Books (See Top 100 in Books)
Acknowledgements.


Preface.


1. Introduction.


1.1 Why randomize clusters?


1.2 What is the impact of cluster randomization on the design and analysis of a trial?


1.3 Quantifying the effect of clustering.


1.4 Randomized versus non-randomized comparisons.


1.5 The unit of inference.


1.6 Terminology: what’s in a name?


2. The historical development of cluster randomized trials.


2.1 Randomized trials before 1950.


2.2 Cluster randomized trials between 1950 and 1978.


2.3 Cluster randomized trails since 1978.


3. Issues arising in the planning of cluster randomization trials.


3.1 Selecting interventions.


3.2 Setting eligibility criteria.


3.3 Measuring subject response.


3.4 The most commonly used experimental designs.


3.5 Factorial and crossover designs.


3.6 Selecting an experimental design.


3.7 The importance of cluster-level replication.


3.8 Strategies for conducting successful trials.


4. The role of informed consent and other ethical issues.


4.1 The risk of harm.


4.2 Informed consent.


4.3 Subject blindness and informed consent.


4.4 Randomized consent designs.


4.5 Ethical issues and trial monitoring.


5. Sample size estimation for cluster randomization designs.


5.1 General issues of sample size estimation.


5.2 The completely randomized design.


5.3 The matched-pair design.


5.4 The stratified design.


5.5 Issues involving losses to follow-up.


5.6 Strategies for achieving desired power.


6. Analysis of binary outcomes.


6.1 Selecting the unit of analysis.


6.2 The completely randomized design.


6.3 The matched-pair design.


6.4 The stratified design.


7. Analysis of quantitative outcomes.


7.1 The completely randomized design.


7.2 The matched-pair design.


7.3 The stratified design.


8. Analysis of count, time to event and categorical outcomes.


8.1 Count and time to event data.


8.2 Categorical data.


9. Reporting of cluster randomization trials.


9.1 Reporting of study design.


9.2 Reporting of study results.


References.


Index.

I am an epidemiologist responsible for designing and overseeing implementation, analysis and reporting of a number of cluster randomized health intervention trials in developing countries. I found this book absolutely terrific for several reasons. First, the scope of the book is broad. This is not just a compilation of statistical methods. The authors discuss the rationale for cluster randomization, its historic development, specific issues that arise in planning the studies, securing informed consent and other ethical issues affected by cluster design. The final chapter reviews the central themes of the book in discussing how to fully report a cluster randomized trial. Throughout these chapters the authors describe both the theoretical issues raised, as well as practical solutions. Second, the book represents a succinct and collected discussion of the relevant issues. As a non-statistician, I don't read the primary statistical literature. I do read health intervention studies that employ a cluster randomized method. I may attend an occasional short seminar on cluster design, or discuss particular issues with collaborating statisticians, but until I read this book, I felt I was freelancing each design and analysis issue. After reading the book I have exposure to the whole paradigm. I can understand the design and analysis choices, make better decisions, and make consultations with my collaborating statisticians more focused and productive. Third, options for analysis, including their assumptions, advantages and disadvantages, as well as methods for calculating sample size are systematically presented. This directly empowers the reader to make balanced and sound decisions about appropriate study size and analytic approach. Fourth, the book is readable.

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