Overview
- Includes examples of a wide variety of common statistical errors and misconceptions in medical data analysis and clinical trial design, with at least one alternative solution for each problem, to provide statistical tools that can be used in practice
- Written in an informal style with technical content kept to a reasonably low level, making it accessible to non-statisticians as well as statisticians
- Is the first book of its kind for the medical research community
Part of the book series: Springer Series in Pharmaceutical Statistics (SSPS)
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
- Hypothesis testing
- Bayesian statistics
- Survival analysis
- P-value
- Clinical trials
- Adaptive randomization
- Phase I Trials
- Confounding
- Expansion cohorts
- Bias correction
- Monitoring toxicity
- Design of medical experiments
- Analysis of medical experiments
- Dose finding
- Dynamic treatment regimes
- Experimental design
- Precision medicine
- Probability
- Randomization
About this book
This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.
Reviews
“This is an excellent book ... written primarily for medical researchers and statisticians working in the medical research sector. ... I'd conclude by extending my hearty congratulations to the author for contributing such a wonderful volume to the biostatistics literature.” (Bibhas Chakraborty, International Statistical Review, Vol. 88 (3), 2020)
“This book can be recommended to a statistician that is starting a career in drug development and pharma research, or a statistician in this area willing to receive some food for thought and foster critical thinking.” (ISCB News, iscb.info, Issue 70, December, 2020)
Authors and Affiliations
About the author
Peter F. Thall is the Anise J. Sorrell Professor at the Department of Biostatistics at M.D. Anderson Cancer Center. He is a Fellow of the American Statistical Association and The Society for Clinical Trials, and received the Owen Award in 2014. He has published over 250 papers and book chapters in the statistical and medical literature, and co-authored the book Bayesian Designs for Phase I-II Clinical Trials. His research areas include clinical trial design, precision medicine, Bayesian nonparametric statistics, incorporating expert opinion in Bayesian inference, and dynamic treatment regimes. He has presented over 200 invited talks and 30 short courses, and has served as an associate editor for Journal of the National Cancer Institute, Statistics in Medicine, Statistics in Biosciences, Clinical Trials, and Biometrics.
Bibliographic Information
Book Title: Statistical Remedies for Medical Researchers
Authors: Peter F. Thall
Series Title: Springer Series in Pharmaceutical Statistics
DOI: https://doi.org/10.1007/978-3-030-43714-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-43713-8Published: 13 March 2020
Softcover ISBN: 978-3-030-43716-9Published: 13 March 2021
eBook ISBN: 978-3-030-43714-5Published: 12 March 2020
Series ISSN: 2366-8695
Series E-ISSN: 2366-8709
Edition Number: 1
Number of Pages: XI, 291
Number of Illustrations: 30 b/w illustrations, 12 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Drug Safety and Pharmacovigilance, Biostatistics, Pharmaceutical Sciences/Technology, Bayesian Inference, Statistical Theory and Methods