Fr. 196.00

Cluster Randomization Trials - Statistical Design and Analysis

English · Hardback

Shipping usually within 3 to 5 weeks

Description

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This books covers all three types of trials resulting in clustered data. For outcome variables of binary, continuous, and time to event types. The methods are discussed in terms of clinical trials, but can be used to design and analyze any types of experiments involving clustered data.


List of contents

Preface 1. Introduction 2. One-Sample Binary Data 3. Chi-Square Test for 2-Sample Clustered Binary Data (I): Donner’s Adjustment 4. Chi-Square Test for 2-Sample Clustered Binary Data (II): GEE Adjustment 5. Subunit Randomization Trials: GEE-Type Test for 2-Sample Clustered Binary Data 6. Random Number Generation of Clustered Binary Data 7. "Tests for R×C Contingency Tables with Clustered Categorical Data" 8. Clustered Continuous Data 9. Inference of Medians for Paired Survival Data 10. "Rank Tests for Matched Survival Data and Sample Size Calculation" 11. "Rank Tests for Clustered Survival Data and Sample Size Calculation under Cluster Randomization" 12. "Rank Tests for Clustered Survival Data and Sample Size Calculation under Subunit Randomization" 13. "Group Sequential Testing for Cluster Randomized Trials with Time-to-Event Endpoint" 14. "Random Number Generation of Clustered Survival Data" 15. Cox’s Regression for Clustered Survival Data 16. Design and Analysis of Individually Randomized Group-Treatment Trials 17. "Analysis of Medical Tests I: Comparison of Concordance Rates with Clustered Data" 18. Comparison of Binary Medical Tests and ROC Curves with Clustered Data

About the author

Sin Ho-Jung is a Professor in the Department of Biostatistics and Bioinformatics at Duke University.

Summary

This books covers all three types of trials resulting in clustered data. For outcome variables of binary, continuous, and time to event types. The methods are discussed in terms of clinical trials, but can be used to design and analyze any types of experiments involving clustered data.

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