Sample Size Calculations in Clinical Research, Third Edition

✍ Scribed by Shein-Chung Chow, Jun Shao, Hansheng Wang, Yuliya Lokhnygina

• Publisher: CRC Press;Chapman and Hall/CRC
• Year: 2017
• Tongue: English
• Leaves: 511
• Series: Chapman & Hall/CRC biostatistics series
• Edition: 3
• Category: Library

✦ Synopsis

Like the well-regarded and bestselling second edition, Sample Size Calculations in Clinical Research, Third Edition, presents statistical procedures for performing sample size calculations during various phases of clinical research and development. This new edition will be updated throughout and will contain four entirely new chapters written especially for this edition

✦ Table of Contents

Content: Cover
Half Title
Published Titles
Title Page
Copyright Page
Contents
Preface
1. Introduction
1.1 Regulatory Requirement
1.1.1 Adequate and Well-Controlled Clinical Trials
1.1.2 Substantial Evidence
1.1.3 Why At Least Two Studies?
1.1.4 Substantial Evidence with a Single Trial
1.1.5 Sample Size
1.2 Basic Considerations
1.2.1 Study Objectives
1.2.2 Study Design
1.2.3 Hypotheses
1.2.3.1 Test for Equality
1.2.3.2 Test for Noninferiority
1.2.3.3 Test for Superiority
1.2.3.4 Test for Equivalence
1.2.3.5 Relationship among Noninferiority, Superiority, and Equivalence. 1.2.4 Primary Study Endpoint1.2.5 Clinically Meaningful Difference
1.3 Procedures for Sample Size Calculation
1.3.1 Type I and Type II Errors
1.3.2 Precision Analysis
1.3.3 Power Analysis
1.3.4 Probability Assessment
1.3.5 Reproducibility Probability
1.3.6 Sample Size Reestimation without Unblinding
1.4 Aims and Structure of this Book
1.4.1 Aim of this Book
1.4.2 Structure of this Book
2. Considerations Prior to Sample Size Calculation
2.1 Confounding and Interaction
2.1.1 Confounding
2.1.2 Interaction
2.1.3 Remark
2.2 One-Sided Test versus Two-Sided Test
2.2.1 Remark. 2.3 Crossover Design versus Parallel Design2.3.1 Intersubject and Intrasubject Variabilities
2.3.2 Crossover Design
2.3.3 Parallel Design
2.3.4 Remark
2.4 Subgroup/Interim Analyses
2.4.1 Group Sequential Boundaries
2.4.2 Alpha Spending Function
2.5 Data Transformation
2.5.1 Remark
2.6 Practical Issues
2.6.1 Unequal Treatment Allocation
2.6.2 Adjustment for Dropouts or Covariates
2.6.3 Mixed-Up Randomization Schedules
2.6.4 Treatment or Center Imbalance
2.6.5 Multiplicity
2.6.6 Multiple-Stage Design for Early Stopping
2.6.7 Rare Incidence Rate
3. Comparing Means. 3.1 One-Sample Design3.1.1 Test for Equality
3.1.2 Test for Noninferiority/Superiority
3.1.3 Test for Equivalence
3.1.4 An Example
3.1.4.1 Test for Equality
3.1.4.2 Test for Noninferiority
3.1.4.3 Test for Equivalence
3.2 Two-Sample Parallel Design
3.2.1 Test for Equality
3.2.2 Test for Noninferority/Superiority
3.2.3 Test for Equivalence
3.2.4 An Example
3.2.4.1 Test for Equality
3.2.4.2 Test for Noninferiority
3.2.4.3 Test for Equivalence
3.2.5 Remarks
3.3 Two-Sample Crossover Design
3.3.1 Test for Equality
3.3.2 Test for Noninferiority/Superiority. 3.3.3 Test for Equivalence3.3.4 An Example
3.3.4.1 Therapeutic Equivalence
3.3.4.2 Noninferiority
3.3.5 Remarks
3.4 Multiple-Sample One-Way ANOVA
3.4.1 Pairwise Comparison
3.4.2 Simultaneous Comparison
3.4.3 An Example
3.4.4 Remarks
3.5 Multiple-Sample Williams Design
3.5.1 Test for Equality
3.5.2 Test for Noninferiority/Superiority
3.5.3 Test for Equivalence
3.5.4 An Example
3.6 Practical Issues
3.6.1 One-Sided versus Two-Sided Test
3.6.2 Parallel Design versus Crossover Design
3.6.3 Sensitivity Analysis
4. Large Sample Tests for Proportions
4.1 One-Sample Design.

✦ Subjects

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