Success Probability Estimation with Applications to Clinical Trials
Author(s): Daniele De Martini (Author)
Publisher: Wiley
Publication Date: 17 May 2013
Edition: 1st
Language: English
Print length: 232 pages
ISBN-10: 1118335783
ISBN-13: 9781118335789
Book Description
Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment
Success Probability Estimation with Applications to Clinical Trials 1st Edition details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests.
Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation.
Success Probability Estimation with Applications to Clinical Trials:
• Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries
Features practical solutions for problems that are often encountered in clinical trials
Includes success probability estimation for widely used statistical tests, such as parametric and nonparametric models
Focuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trials
Introduces statistical concepts related to success probability estimation and their usefulness in clinical trials
Success Probability Estimation with Applications to Clinical Trials 1st Edition is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.
Editorial Reviews
From the Inside Flap
Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment
Success Probability Estimation with Applications to Clinical Trials 1st Edition details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests.
Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation.
Success Probability Estimation with Applications to Clinical Trials:
Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries
Features practical solutions for problems that are often encountered in clinical trials
Includes success probability estimation for widely used statistical tests, such as parametric and nonparametric models
Focuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trials
Introduces statistical concepts related to success probability estimation and their usefulness in clinical trials
Success Probability Estimation with Applications to Clinical Trials 1st Edition is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.
From the Back Cover
Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment
Success Probability Estimation with Applications to Clinical Trials 1st Edition details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests.
Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation.
Success Probability Estimation with Applications to Clinical Trials:
Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries
Features practical solutions for problems that are often encountered in clinical trials
Includes success probability estimation for widely used statistical tests, such as parametric and nonparametric models
Focuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trials
Introduces statistical concepts related to success probability estimation and their usefulness in clinical trials
Success Probability Estimation with Applications to Clinical Trials 1st Edition is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.
About the Author
DANIELE DE MARTINI, PhD, is Assistant Professor in the Department of Statistics and Quantitative Methods at the University of Milano-Bicocca in Italy. He is also a member of the American Statistical Association, Society for Clinical Trials, and Italian Statistical Society.