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Author: Heping Zhang
Publisher: Springer Science & Business Media
ISBN: 9780387986715
Category : Science
Languages : en
Pages : 252
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Book Description
A demonstration of the recursive partitioning methodology and its effectiveness as a response to the challenge of analysing and interpreting multiple complex pathways to many illnesses, diseases, and ultimately death. For comparison purposes, standard regression methods are presented briefly and then applied in the examples. This book is suitable for three broad groups of readers: biomedical researchers, clinicians, public health practitioners including epidemiologists, health service researchers, and environmental policy advisers; consulting statisticians who can use the recursive partitioning technique as a guide in providing effective and insightful solutions to clients'problems; and statisticians interested in methodological and theoretical issues. The book provides an up-to-date summary of the methodological and theoretical underpinnings of recursive partitioning, as well as a host of unsolved problems the solutions of which would advance the rigorous underpinnings of statistics in general.
Author: Heping Zhang
Publisher: Springer Science & Business Media
ISBN: 9780387986715
Category : Science
Languages : en
Pages : 252
Get Book Here
Book Description
A demonstration of the recursive partitioning methodology and its effectiveness as a response to the challenge of analysing and interpreting multiple complex pathways to many illnesses, diseases, and ultimately death. For comparison purposes, standard regression methods are presented briefly and then applied in the examples. This book is suitable for three broad groups of readers: biomedical researchers, clinicians, public health practitioners including epidemiologists, health service researchers, and environmental policy advisers; consulting statisticians who can use the recursive partitioning technique as a guide in providing effective and insightful solutions to clients'problems; and statisticians interested in methodological and theoretical issues. The book provides an up-to-date summary of the methodological and theoretical underpinnings of recursive partitioning, as well as a host of unsolved problems the solutions of which would advance the rigorous underpinnings of statistics in general.
Author: Heping Zhang
Publisher: Springer Science & Business Media
ISBN: 1441968245
Category : Mathematics
Languages : en
Pages : 267
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Book Description
Multiple complex pathways, characterized by interrelated events and c- ditions, represent routes to many illnesses, diseases, and ultimately death. Although there are substantial data and plausibility arguments suppo- ing many conditions as contributory components of pathways to illness and disease end points, we have, historically, lacked an e?ective method- ogy for identifying the structure of the full pathways. Regression methods, with strong linearity assumptions and data-basedconstraints onthe extent and order of interaction terms, have traditionally been the strategies of choice for relating outcomes to potentially complex explanatory pathways. However, nonlinear relationships among candidate explanatory variables are a generic feature that must be dealt with in any characterization of how health outcomes come about. It is noteworthy that similar challenges arise from data analyses in Economics, Finance, Engineering, etc. Thus, the purpose of this book is to demonstrate the e?ectiveness of a relatively recently developed methodology—recursive partitioning—as a response to this challenge. We also compare and contrast what is learned via rec- sive partitioning with results obtained on the same data sets using more traditional methods. This serves to highlight exactly where—and for what kinds of questions—recursive partitioning–based strategies have a decisive advantage over classical regression techniques.
Author: Heping Zhang
Publisher:
ISBN: 9781475730289
Category :
Languages : en
Pages : 240
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Book Description
Author: Heping Zhang
Publisher: Springer Science & Business Media
ISBN: 1475730276
Category : Science
Languages : en
Pages : 229
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Book Description
A demonstration of the recursive partitioning methodology and its effectiveness as a response to the challenge of analysing and interpreting multiple complex pathways to many illnesses, diseases, and ultimately death. For comparison purposes, standard regression methods are presented briefly and then applied in the examples. This book is suitable for three broad groups of readers: biomedical researchers, clinicians, public health practitioners including epidemiologists, health service researchers, and environmental policy advisers; consulting statisticians who can use the recursive partitioning technique as a guide in providing effective and insightful solutions to clients'problems; and statisticians interested in methodological and theoretical issues. The book provides an up-to-date summary of the methodological and theoretical underpinnings of recursive partitioning, as well as a host of unsolved problems the solutions of which would advance the rigorous underpinnings of statistics in general.
Author: Carol D. Ryff
Publisher: Oxford University Press
ISBN: 0190676396
Category : Psychology
Languages : en
Pages : 553
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Book Description
Most health research to date has been pursued within the confines of scientific disciplines that are guided by their own targeted questions and research strategies. Although useful, such inquiries are inherently limited in advancing understanding the interplay of wide-ranging factors that shape human health. The Oxford Handbook of Integrative Health Science embraces an integrative approach that seeks to put together sociodemographic factors (age, gender, race, socioeconomic status) known to contour rates of morbidity and mortality with psychosocial factors (emotion, cognition, personality, well-being, social connections), behavioral factors (health practices) and stress exposures (caregiving responsibilities, divorce, discrimination) also known to influence health. A further overarching theme is to explicate the biological pathways through which these various effects occur. The biopsychosocial leitmotif that inspires this approach demands new kinds of studies wherein wide-ranging assessments across different domains are assembled on large population samples. The MIDUS (Midlife in the U.S.) national longitudinal study exemplifies such an integrative study, and all findings presented in this collection draw on MIDUS. The way the study evolved, via collaboration of scientists working across disciplinary lines, and its enthusiastic reception from the scientific community are all part of the larger story told. Embedded within such tales are important advances in the identification of key protective or vulnerability factors: these pave the way for practice and policy initiatives seeking to improve the nation's health.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1522519343
Category : Social Science
Languages : en
Pages : 2104
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Book Description
The growing presence of discrimination and isolation has caused negative changes to human interactions. With the ubiquity of these practices, there is now an increasingly urgent need to close this divide. Discrimination and Diversity: Concepts, Methodologies, Tools, and Applications provides a critical look at race, gender, and modern day discrimination and solutions to creating sustainable diversity across numerous contexts and fields. Including innovative studies on anti-discrimination measures, gender discrimination, and tolerance, this multi-volume book is an ideal source for professionals, practitioners, graduate students, academics, and researchers working in equality, as well as managers and those in leadership roles.
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 013389214X
Category : Business & Economics
Languages : en
Pages : 437
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Book Description
Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
Author: Ying Lu
Publisher: World Scientific
ISBN: 9814583324
Category : Medical
Languages : en
Pages : 1471
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Book Description
The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch.The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field.Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research.
Author: John Maindonald
Publisher: Cambridge University Press
ISBN: 1139486675
Category : Computers
Languages : en
Pages : 565
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Book Description
Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.
Author: Manfred Schwaiger
Publisher: Springer Science & Business Media
ISBN: 364255721X
Category : Computers
Languages : en
Pages : 547
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Book Description
This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The reader will find numerous ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining, medicine and biological sciences as well as marketing, finance and management sciences.
