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Introduction to Randomized Controlled Clinical Trials, Second Edition
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Table of Contents

WHAT IS A RANDOMIZED CONTROLLED TRIAL?
Definition and Key Features
Historical Context and the Nature of RCTS
Structure and Justification of RCTs
Exercises

BIAS
What is meant by bias in RCTs?
Types of Bias
Exercises

HOW MANY PATIENTS DO I NEED?
Criteria for Sample Size Calculations
Hypothesis Tests
Sample Size for a Normally Distributed Variable
Sample Size for a Binary Variable
General Remarks About Sample Size Calculations
Exercises

METHODS OF ALLOCATION
Simple Randomization
Random Permuted Blocks
Biased Coin Designs and Urn Schemes
Unequal Randomization
Stratification
Minimization
Exercises

ASSESSMENT, BLINDING AND PLACEBOS
Double and Single Blindness
Placebos
Practical Considerations
Exercises

ANALYSIS OF RESULTS
Example
Use of Confidence Intervals
Baselines: Uses and Abuses
Analysis of Covariance
Exercises

FURTHER ANALYSIS: BINARY AND SURVIVAL DATA
Binary Data: An Example and a Statistical Model
Point Estimates and Hypothesis Tests
Interval Estimates for the Binary Case
Adjusting Binary Outcomes for Baseline Observations
Survival Analysis
Analyses Using Randomization Models
Exercises

MONITORING ACCUMULATING DATA
Motivation and Problems with Repeated Analysis of Data
Sequential and Group-Sequential Methods
Other Approaches to Accumulating Data
Data Monitoring Committees
Exercises
SUBGROUPS AND MULTIPLE OUTCOMES
The Role of Sub-groups in Randomized Clinical Trials
Methods for Comparing Sub-groups
Methods of Selecting Sub-groups
Qualitative Interactions
Multiple outcomes
Correction of P-values
Some Alternative Methods for Multiple Outcomes
Exercises

PROTOCOLS AND PROTOCOL DEVIATIONS
Protocols: Their Nature and Role
Protocol Deviation
Analysis by Intention-to-Treat
Exercises

SOME SPECIAL DESIGNS: CROSSOVERS, EQUIVALENCE AND CLUSTERS
Crossover Trials and Parallel Group Trials
The AB/BA Design
Analysis of AB/BA Design for Continuous Outcomes
The Issue of Carryover
Equivalence Trials
Cluster Randomized Trials
Exercises

META-ANALYSES OF CLINICAL TRIALS
What Are Meta-Analyses and Why Are They Needed?
Some Methodology for Meta-Analysis
Some Graphical Methods for Meta-Analysis
Some General Issues in Meta-Analysis
Exercises

FURTHER READING
SOLUTIONS TO EXERCISES
REFERENCES

Reviews

"...this book is very well presented and ... is extremely pleasant and enjoyable to read. Both the statistical concepts and medical examples are very well explained. I highly recommend this book as a course text and as an excellent reference book for anyone interested in clinical trials. A copy of it should certainly appear in every university library."
-Journal of Applied Statistics, 2007

"...a very welcome revision. The author has drawn upon his experiences to provide a valuable account of the important statistical underpinnings of the randomized clinical trial. ... written primarily for students of statistics ... highly desirable ... ideal for its intended audience."
-Susan Todd, The University of Reading, UK

"...The second edition builds upon the first by adding a chapter on binary and survival data and updating the chapter on balancing treatment allocations. Whether you might need to introduce a novice to the unique principles and pitfalls of clinical trials or remind an experienced statistician of their importance, this book would serve your purpose admirably. Moreover, as an experienced clinical trialist, I found it to be an excellent reminder of the statistical principles and concepts that underlie the day-to-day rules of our profession. ... Throughout, the author discusses principles, concepts and applications with a clarity that will be truly appreciated by those trained in mathematics. Each chapter focuses on a key challenge in the analysis of clinical trials and its associated statistical implications. ... Overall, the choice of chapter topics is comprehensive and well chosen. ... This text is definitely a handy reference-certainly worthwhile for a statistically conversant audience who are lacking in clinical trials experience. Such an audience will find this book educational and the author's concise style, an easy read. I would definitely recommend it for the bookshelf of anyone working in clinical trials."
-Karen Kesler, Journal of Biopharmaceutical Statistics, Issue 5, 2007

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