{"product_id":"9780470660959","title":"Binary Data Analysis of Randomized Clinical Trials with Noncompliance","description":"\u003ch3\u003eStatistics in Practice\u003c\/h3\u003e\u003ch1\u003eBinary Data Analysis of Randomized Clinical Trials with Noncompliance\u003c\/h1\u003e\u003ch3\u003eKung-Jong Lui\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMedical \/ Clinical Medicine\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003eIt 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\n\u003c\/div\u003e\u003cdiv\u003e \u003cb\u003eKung-Jong Lui\u003c\/b\u003e, Department of Mathematics and Statistics, San Diego State University, USA.\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e02 May 2011\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9780470660959\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e330\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e22.08\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44315359608972,"sku":"9780470660959","price":105.26,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780470660959.jpg?v=1780109808","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9780470660959","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}