Chul Ahn, PhD, is a professor in the Department of Clinical Sciences and the cancer center associate director for biostatistics and bioinformatics in the Simmons Comprehensive Cancer Center at the University of Texas Southwestern Medical Center. He is also director of Biostatistics and Research Design for the NIH-sponsored Clinical and Translational Science Award (CTSA). He has published more than 370 peer-reviewed papers addressing the design and analysis of clinical trials and epidemiological studies as well as the evaluation of repeated measurements and correlated data. Moonseong Heo, PhD, is a professor in the Department of Epidemiology & Population Health at the Albert Einstein College of Medicine. His research includes sample size determinations for clinical trials, meta-analysis, longitudinal data analysis applying mixed-effects models, handling attrition problems in clinical trials data, and epidemiology in the fields of obesity and psychiatry. Song Zhang, PhD, is an associate professor in the Department of Clinical Sciences at the University of Texas Southwestern Medical Center. He has extensive experience in the design of clinical trials with correlated outcomes, addressing challenges that involve different correlation structures, missing data patterns, financial constraints, and historical controls. He is also interested in Bayesian statistical methods and their application in longitudinal and survival data analysis, high-throughput data analysis, disease mapping, adaptive design for clinical trials, and missing data imputation.
...an excellent resource for both statisticians and practitioners undertaking prospective studies in human trials. -International Statistical Review . . . this is a clearly written and sequentially well-organized book. One may find it easy to read and comprehend the various conceptual and methodological issues. To facilitate better understanding, each of the covered topic deals with illustration. I fully agree with the claim of the authors that this book may serve as a useful resource for biostatisticians, clinical investigators, epidemiologists, and social scientists whose research involves randomized trials with correlated outcomes usually classified into two types: clustered or longitudinal. -Sada Nand Dwivedi, International Society for Clinical Biostatistics The book opens with an excellent summary and overview of conventional sample size analysis, including precision and power analysis. . . The book moves on to sample size calucations for clustered data. -The American Statistician, 2016 This book aims to be a useful reference for those of us who are frequently asked 'how many people will I need to recruit?' This text provides a useful reference for those who wish to calculate the sample size for a clustered design . . . clear and accessible examples and some thoughtful reminders of key considerations. -Beth Stuart, International Society for Clinical Biostatistics