{"product_id":"binary-data-analysis-of-randomized-clinical-trials-with-noncompliance-isbn-9780470660959","title":"Binary Data Analysis of Randomized Clinical Trials with Noncompliance","description":"It is quite common in a randomized clinical trial (RCT) to encounter patients who 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 of the treatment efficacy.  \u003cp\u003eThis 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 series of 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eKey features:\u003c\/b\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eConsort-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.\u003c\/li\u003e \u003cli\u003eReal-life examples are used throughout the book to explain the practical usefulness of test procedures and estimators.\u003c\/li\u003e \u003cli\u003eEach chapter is self-contained, allowing the book to be used as a reference source.\u003c\/li\u003e \u003cli\u003eIncludes SAS programs which can be easily modified in calculating the required sample size.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eBiostatisticians, 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.\u003c\/p\u003e  \u003cb\u003ePreface.\u003c\/b\u003e A bout the author.  \u003cp\u003e\u003cb\u003e1 Randomized clinical trials with noncompliance: issues, definitions and problems of commonly used analyses\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003e1.1 Randomized encouragement design (RED).\u003c\/p\u003e \u003cp\u003e1.2 Randomized consent designs.\u003c\/p\u003e \u003cp\u003e1.3 Treatment efficacy versus programmatic effectiveness.\u003c\/p\u003e \u003cp\u003e1.4 Definitions of commonly used terms and assumptions.\u003c\/p\u003e \u003cp\u003e1.5 Mmost commonly used analyses for a RCT with noncompliance.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Randomized clinical trials with noncompliance under parallel groups design\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003e2.1 Testing superiority.\u003c\/p\u003e \u003cp\u003e2.2 Testing noninferiority.\u003c\/p\u003e \u003cp\u003e2.3 Testing equivalence.\u003c\/p\u003e \u003cp\u003e2.4 Interval estimation.\u003c\/p\u003e \u003cp\u003e2.5 Sample size determination.\u003c\/p\u003e \u003cp\u003e2.6 Risk model-based approach.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eAppendix.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Randomized clinical trials with noncompliance in stratified sampling\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003e3.1 Testing superiority.\u003c\/p\u003e \u003cp\u003e3.2 Testing noninferiority.\u003c\/p\u003e \u003cp\u003e3.3 Testing equivalence .\u003c\/p\u003e \u003cp\u003e3.4 Interval estimation.\u003c\/p\u003e \u003cp\u003e3.5 Test homogeneity of index in large strata.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eAppendix.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Randomized clinical trials with noncompliance under cluster sampling\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003e4.1 Testing superiority.\u003c\/p\u003e \u003cp\u003e4.2 Testing noninferiority.\u003c\/p\u003e \u003cp\u003e4.3 Testing equivalence.\u003c\/p\u003e \u003cp\u003e4.4 Interval estimation.\u003c\/p\u003e \u003cp\u003e4.5 Sample size determination.\u003c\/p\u003e \u003cp\u003e4.6 An alternative randomization-based approach.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eAppendix.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Randomized clinical trials with both noncompliance and subsequent missing outcomes.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Testing superiority.\u003c\/p\u003e \u003cp\u003e5.2 Testing noninferiority.\u003c\/p\u003e \u003cp\u003e5.3 Testing equivalence.\u003c\/p\u003e \u003cp\u003e5.4 Interval estimation.\u003c\/p\u003e \u003cp\u003e5.5 Sample size determination.\u003c\/p\u003e \u003cp\u003e5.6 An alternative missing at random (MAR) model.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eAppendix.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Randomized clinical trials with noncompliance in repeated binary measurements\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003e6.1 Testing superiority.\u003c\/p\u003e \u003cp\u003e6.2 Testing noninferiority.\u003c\/p\u003e \u003cp\u003e6.3 Testing equivalence.\u003c\/p\u003e \u003cp\u003e6.4 Interval estimation.\u003c\/p\u003e \u003cp\u003e6.5 Sample size determination.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eReferences\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex\u003c\/b\u003e.\u003c\/p\u003e \"The book would be well-suited as a reference for biostatisticians, clinicians, researchers, and data analysts - and it would be useful as supplemental reading for academic courses in a variety of related fields.\" (Book News, 1 August 2011) \u003cb\u003eKung-Jong Lui\u003c\/b\u003e, Department of Mathematics and Statistics, San Diego State University, USA.  It is quite common in a randomized clinical trial (RCT) to encounter patients who 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 of the treatment efficacy.  \u003cp\u003eThis 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 series of 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.\u003c\/p\u003e \u003cp\u003eKey features:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eConsort-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.\u003c\/li\u003e \u003cli\u003eReal-life examples are used throughout the book to explain the practical usefulness of test procedures and estimators.\u003c\/li\u003e \u003cli\u003eEach chapter is self-contained, allowing the book to be used as a reference source.\u003c\/li\u003e \u003cli\u003eIncludes SAS programs which can be easily modified in calculating the required sample size.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eBiostatisticians, 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.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988811923685,"sku":"NP9780470660959","price":112.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470660959.jpg?v=1761781688","url":"https:\/\/k12savings.com\/es\/products\/binary-data-analysis-of-randomized-clinical-trials-with-noncompliance-isbn-9780470660959","provider":"K12savings","version":"1.0","type":"link"}