Matthews Introduction to Randomized Controlled Clinical Trials, Second Edition

2. Auflage 2010
ISBN: 978-1-4200-1130-2
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 302 Seiten

Reihe: Chapman & Hall/CRC Texts in Statistical Science

Evidence from randomized controlled clinical trials is widely accepted as the only sound basis for assessing the efficacy of new medical treatments. Statistical methods play a key role in all stages of these trials, including their justification, design, and analysis. This second edition of Introduction to Randomized Controlled Clinical Trials provides a concise presentation of the principles applied in this area. It details the concepts behind randomization and methods for designing and analyzing trials and also includes information on meta-analysis and specialized designs, such as cross-over trials, cluster-randomized designs, and equivalence studies.

This latest edition features new and revised references, examples, exercises, and a new chapter dedicated to binary outcomes and survival analysis. It also presents numerous examples taken from the medical literature, contains exercises at the end of each chapter, and offers solutions in an appendix. The author uses Minitab and R software throughout the text for implementing the methods that are presented.

Comprehensive and accessible, Introduction to Randomized Controlled Clinical Trials is well-suited for those familiar with elementary statistical ideas and methods who want to further their knowledge of the subject.

Zielgruppe

Advanced undergraduate and graduate students in statistics, biostatistics, and mathematics, medical science researchers, and statisticians working on clinical trials in healthcare and the pharmaceutical industry.

Autoren/Hrsg.

Matthews, John N.S.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie

Inhaltsverzeichnis

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