Binary data analysis of randomized clinical trials with noncompliance

It is quite common in a randomized clinical trial (RCT) to encounter patientswho do not comply with their assigned treatment. Since noncompliance often occurs non-randomly, the commonly-used approaches, including both the as-treated(AT) and as-protocol (AP) analysis, and the intent-to-treat (ITT) (or as-randomized) analysis, are all well known to possibly produce a biased inference ofthe treatment efficacy. This book provides a systematic and organized approach to analyzing data for RCTs with noncompliance under the most frequently-encountered situations. These include parallel sampling, stratified sampling, cluster sampling, parallel sampling with subsequent missing outcomes, and a seriesof dependent Bernoulli sampling for repeated measurements. The author provides a comprehensive approach by using contingency tables to illustrate the latent probability structure of observed data. Using real-life examples, computer-simulated data and exercises in each chapter, the book illustrates the underlying theory in an accessible, and easy to understand way. Key features: Consort-flow diagrams and numerical examples are used to illustrate the bias of commonly used approaches, such as, AT analysis, AP analysis and ITT analysis for a RCT with noncompliance. Real-life examples are used throughout the book to explain the practical usefulness of test procedures and estimators. Each chapter is self-contained, allowing the book to be used as a reference source. IncludesSAS programs which can be easily modified in calculating the required sample size. Biostatisticians, clinicians, researchers and data analysts working in pharmaceutical industries will benefit from this book. This text can also be used as supplemental material for a course focusing on clinical statistics or experimental trials in epidemiology, psychology and sociology. INDICE: About the author Preface Chapter 1 Randomized Clinical Trials withNoncompliance: Issues, Definitions and Problems of Commonly-Used Analyses 1.1Randomized Encouragement Design (RED)1.2 Randomized Consent Designs1.3 Treatment Efficacy Versus Programmatic Effectiveness1.4 Definitions of Commonly-UsedTerms and Assumptions1.5 Most Commonly-Used Analyses for a RCT with NoncomplianceExercises Chapter 2 Randomized Clinical Trials with Noncompliance under Parallel Groups Design 2.1 Testing Superiority2.2 Testing Non-inferiority2.3 Testing Equivalence2.4 Interval Estimation2.5 Sample Size Determination2.6 Risk Model-Based ApproachExercisesAppendixChapter 3 Randomized Clinical Trials with Noncompliance in Stratified Sampling 3.1 Testing Superiority3.2 Testing Non-inferiority3.3 Testing Equivalence 3.4 Interval Estimation3.5 Test Homogeneity of Index in Large StrataExercisesAppendixChapter 4 Randomized Clinical Trials with Noncompliance under Cluster Sampling 4.1 Testing Superiority4.2 Testing Non-inferiority4.3 Testing Equivalence 4.4 Interval Estimation4.5 Sample Size Determination4.6 An Alternative Randomization-Based Approach ExerciseAppendix Chapter 5 Randomized Clinical Trials with Both Noncompliance and Subsequent Missing Outcomes5.1 Testing Superiority5.2 Testing Non-inferiority5.3 Testing Equivalence 5.4 Interval Estimation5.5 Sample Size Determination5.6 An AlternativeMissing at Random (MAR) ModelExercise Appendix Chapter 6 Randomized Clinical Trials with Noncompliance in Repeated Binary Measurements 6.1 Testing Superiority6.2 Testing Non-Inferiority6.3 Testing Equivalence6.4 Interval Estimation6.5 Sample Size DeterminationExercises References Index

• ISBN: 978-0-470-66095-9
• Editorial: John Wiley & Sons
• Encuadernacion: Cartoné
• Páginas: 320
• Fecha Publicación: 01/04/2011
• Nº Volúmenes: 1
• Idioma: Inglés