Sample Size Calculations in Clinical Research: (Chapman & Hall/CRC Biostatistics Series)

Sample size calculation plays an important role in clinical research. It is not uncommon, however, to observe discrepancies among study objectives (or hypotheses), study design, statistical analysis (or test statistic), and sample size calculation. Focusing on sample size calculation for studies conducted during the various phases of clinical research and development, Sample Size Calculation in Clinical Research explores the causes of discrepancies and how to avoid them. This volume provides formulas and procedures for determination of sample size required not only for testing equality, but also for testing non-inferiority/superiority, and equivalence (similarity) based on both untransformed (raw) data and log-transformed data under a parallel-group design or a crossover design with equal or unequal ratio of treatment allocations. It contains a comprehensive and unified presentation of statistical procedures for sample size calculation that are commonly employed at various phases of clinical development. Each chapter includes, whenever possible, real examples of clinical studies from therapeutic areas such as cardiovascular, central nervous system, anti-infective, oncology, and women's health to demonstrate the clinical and statistical concepts, interpretations, and their relationships and interactions. The book highlights statistical procedures for sample size calculation and justification that are commonly employed in clinical research and development. It provides clear, illustrated explanations of how the derived formulas and/or statistical procedures can be used.

Table of Contents:
INTRODUCTION Regulatory Requirement Basic Considerations Procedures for Sample Size Calculation Aims and Structure of the Book CONSIDERATIONS PRIOR TO SAMPLE SIZE CALCULATION Confounding and Interaction One-Sided Test Versus Two-Sided Test Crossover Design Versus Parallel Design Subgroup/Interim Analyses Data Transformation Practical Issues COMPARING MEANS One-Sample Design Two-Sample Parallel Design Two-Sample Crossover Design Multiple-Sample One-Way ANOVA Multiple-Sample Williams Design Practical Issues LARGE SAMPLE TESTS FOR PROPORTIONS One-Sample Design Two-Sample Parallel Design Two-Sample Crossover Design One-Way Analysis of Variance Williams Design Relative Risk - Parallel Design Relative Risk - Crossover Design Practical Issues EXACT TESTS FOR PROPORTIONS Binomial Test Fisher's Exact Test Optimal Multiple-Stage Designs for Single Arm Trials Flexible Designs for Multiple-Arm Trials Remarks TESTS FOR GOODNESS-OF-FIT AND CONTINGENCY TABLES Tests for Goodness-of-Fit Test for Independence -Single Stratum Test for Independence -Multiple Strata Test for Categorical Shift Carry-Over Effect Test Practical Issues COMPARING TIME-TO-EVENT DATA Basic Concepts Exponential Model Cox's Proportional Hazards Model Weighted Log-Rank Test Practical Issues GROUP SEQUENTIAL METHODS Pocock's Test O'Brien and Fleming's Test Wang and Tsiatis' Test Inner Wedge Test Binary Variables Time-to-Event Data Alpha Spending Function Sample Size Re-Estimation Conditional Power Practical Issues COMPARING VARIABILITIES Comparing Intra-Subject Variabilities Comparing Intra-Subject CVs Comparing Inter-Subject Variabilities Comparing Total Variabilities Practical Issues BIOEQUIVALENCE TESTING Bioequivalence Criteria Average Bioequivalence Population Bioequivalence Individual Bioequivalence In Vitro Bioequivalence NONPARAMETRICS Violation of Assumptions One-Sample Location Problem Two-Sample Location Problem Test for Independence Practical Issues SAMPLE SIZE CALCULATION IN OTHER AREAS Dose Response Studies ANOVA with Repeated Measures Quality of Life Bridging Studies Vaccine Clinical Trials Appendix: Tables of Quantiles References Index