Success Probability Estimation with Applications to Clinical Trials

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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 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 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.

Content:
Chapter 1 Basic Statistical Tools (pages 3–24):
Chapter 2 Reproducibility Probability Estimation (pages 25–51):
Chapter 3 Sample Size Estimation (pages 53–90):
Chapter 4 Robustness and Corrections in Sample Size Estimation (pages 91–104):
Chapter 5 General Parametric SP Estimation (pages 107–114):
Chapter 6 SP Estimation for Student's t Statistical Tests (pages 115–123):
Chapter 7 SP Estimation for Gaussian Distributed Test Statistics (pages 125–133):
Chapter 8 SP Estimation for Chi?Square Statistical Tests (pages 135–144):
Chapter 9 General Nonparametric SP Estimation ? with Applications to the Wilcoxon Test (pages 145–162):

Author(s): Daniele De Martini(auth.)
Year: 2013

Language: English
Pages: 215
Tags: Медицинские дисциплины;Социальная медицина и медико-биологическая статистика;