{"title":"Stef Van Buuren","description":"\u003cp\u003eDelve into the world of Stef Van Buuren, where compelling narratives and insightful characters await. Perfect for readers seeking fresh voices, explore these captivating stories and discover your next favourite author.\u003c\/p\u003e","products":[{"product_id":"flexible-imputation-of-missing-data-book-stef-van-buuren-9781439868249","title":"Flexible Imputation of Missing Data","description":"Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science—multiple imputation—fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which are missing data problems in disguise.    Flexible Imputation of Missing Data is supported by many examples using real data taken from the author's vast experience of collaborative research, and presents a practical guide for handling missing data under the framework of multiple imputation. Furthermore, detailed guidance of implementation in R using the author’s package MICE is included throughout the book.      Assuming familiarity with basic statistical concepts and multivariate methods, Flexible Imputation of Missing Data is intended for two audiences:         (Bio)statisticians, epidemiologists, and methodologists in the social and health sciences Substantive researchers who do not call themselves statisticians, but who possess the necessary skills to understand the principles and to follow the recipes         This graduate-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by a verbal statement that explains the formula in layperson terms. Readers less concerned with the theoretical underpinnings will be able to pick up the general idea, and technical material is available for those who desire deeper understanding. The analyses can be replicated in R using a dedicated package developed by the author.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50376421507345,"sku":"CIN1439868247G","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1439868247.jpg?v=1751147256"},{"product_id":"flexible-imputation-of-missing-data-second-edition-book-stef-van-buuren-9781138588318","title":"Flexible Imputation of Missing Data, Second Edition","description":"Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem.  This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field.  This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. 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The D-score presents a unified framework that places children and their developmental milestones from different tools onto the same scale, enabling comparisons in child development across populations, groups and individuals. This pioneering text explains why we need the D-score, how we construct it, and how we calculate it. It will be of interest not just to professionals in child development, but also to policymakers in international settings and to data scientists.   Open Plus Books are published on an F1000-powered open research platform where they can be amended, updated, and extended, in addition to being published as a print and open access ebook. The Open Plus Book version of this book, available at gatesopenresearch.org\/dscore, and the Open Access version of this book, available at www.taylorfrancis.com, have been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license. 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