Introduction to Randomized Controlled Clinical Trials

Introduction to Randomized Controlled Clinical Trials

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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.
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Product details

  • Paperback | 302 pages
  • 152.4 x 228.6 x 17.8mm | 430.92g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • Revised
  • 2nd Revised edition
  • 50 black & white illustrations
  • 1584886242
  • 9781584886242
  • 537,600

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
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