Introduction to Statistical Methods for Clinical Trials: 1st Edition (Hardback) book cover

Introduction to Statistical Methods for Clinical Trials

1st Edition

Edited by Thomas D. Cook, David L. DeMets

Chapman and Hall/CRC

464 pages | 4 B/W Illus.

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pub: 2007-11-19
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Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial.

After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals.

Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.


… There is much good material in this book. The individual chapters are well written and cover the technical aspects as well. A major strength is the ordering of topics to follow the thought process used in the development and implementation of a protocol from defining the question to reporting results. There are careful discussions on fundamental principles and the pivotal role played by statistics is well brought out. … there is much that practicing pharmaceutical statisticians will find useful in this book. They will find the coverage of fundamental principles useful and the technical content of the book a good reference source. …

Pharmaceutical Statistics, 2010

… fits the need for a contemporary text and handbook that is oriented toward the clinical trial statistician. I highly recommend it and look forward to using it as both a primary and supplemental text in our curriculum, as well as a research resource.

—James J. Dignam, University of Chicago, JASA, March 2009

The (technical) statistical content is the main focus of the book and this is what helps it to stand apart from most others on clinical trials (even the more obviously statistically orientated ones). It takes the reader to quite a technical background that would serve him or her well if moving on to research problems in the various areas covered, yet does not lose sight of practical issues. … For those of us with the interest (and need) to grapple with these more statistical issues, I wholeheartedly recommend it.

Biometrics, December 2008

…The book is very well written and clear. … the authors generally strike the right balance for the intended audience. The inclusion of many historically important as well as contemporary examples to illustrate various points throughout the text is a major strength, as is the inclusion of several modern topics not seen in other texts. As a basis for a course in clinical trials for graduate students in biostatistics, this book is outstanding. In addition, statisticians in the pharmaceutical industry, government, or academia … will find this text extremely informative and useful.”

—Michael P. McDermott, University of Rochester Medical Center, Journal of Biopharmaceutical Statistics, 2008

Table of Contents


Introduction to Clinical Trials

History and Background

Ethics of Clinical Research

Types of Research Design and Types of Trials

The Need for Clinical Trials

The Randomization Principle

Timing of a Clinical Trial

Trial Organization

Protocol and Manual of Operations

Regulatory Issues

Overview of the Book

Defining the Question

Statistical Framework

Elements of Study Question

Outcome or Response Measures

The Surrogate Outcome

Composite Outcomes



Study Design

Early Phase Trials

Phase III/IV Trials

Non-Inferiority Designs

Screening, Prevention, and Therapeutic Designs

Adaptive Designs



Sample Size

Sample Size versus Information

A General Setup for Frequentist Designs

Loss to Follow-up and Non-Adherence

Survival Data

Clustered Data

Tests for Interaction

Equivalence/Non-Inferiority Trials

Other Considerations



The Role of Randomization

Fixed Randomization Procedures

Treatment- and Response-Adaptive Randomization Procedures

Covariate-Adaptive Randomization Procedures

Summary and Recommendations


Data Collection and Quality Control

Planning for Collection of Clinical Trial Data

Categories of Clinical Data

Data Quality Control


Survival Analysis


Estimation of Survival Distributions

Comparison of Survival Distributions

Regression Models

Composite Outcomes



Longitudinal Data

A Clinical Longitudinal Data Example

The Subject-Specific Model

Two-Stage Estimation

The Random-Effects, Subject-Specific Model

The Population-Average (Marginal) Model

Restricted Maximum Likelihood Estimation (REML)

Standard Errors


Additional Levels of Clustering

Generalized Estimating Equations for Non-Normal Data

Missing Data


Quality of Life

Defining QoL

Types of QoL Assessments

Selecting a QoL Instrument

Developing a QoL Instrument

Quality of Life Data

Analysis of QoL Data


Data Monitoring and Interim Analysis

Data and Safety Monitoring


The Repeated Testing Problem

Group Sequential Tests

Triangular Test

Curtailment Procedures

Inference Following Sequential Tests



Selected Issues in the Analysis

Bias in the Analysis of Clinical Trial Data

Choice of Analysis Population

Missing Data

Subgroup Analyses

Multiple Testing Procedures



Closeout and Reporting

Closing out a Trial

Reporting Trial Results


Appendix: Delta Method, Maximum Likelihood Theory, and Information

Delta Method

Asymptotic Theory for Likelihood-Based Inference

Hypothesis Testing

Computing the MLE


Brownian Motion



About the Series

Chapman & Hall/CRC Texts in Statistical Science

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Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
MEDICAL / Pharmacology
MEDICAL / Biostatistics