Multilevel Modelling of Health Statistics
Multilevel Modelling of Health Statistics

Author: A. H. Leyland

Publisher: Wiley

Published: 2001-03-30

Total Pages: 0

ISBN-13: 9780471998907

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Multilevel modelling facilitates the analysis of hierarchical data where observations may be nested within higher levels of classification. In health care research, for example, a study may be undertaken to determine the variability of patient outcomes where these also vary by hospital or health care region. Inference can then be made on the efficacy of health care practices. This book provides the reader with the analytical techniques required to study such data sets. * First book to focus on multilevel modelling for health and medical research * Covers the majority of analytical techniques required by health care professionals * Unifies the literature on multilevel modelling for medical and health researchers * Each contribution comes from a specialist in that area Guiding the reader through various stages, from a basic introduction through to methodological extensions and generalised linear models, this test will show how various kinds of data can be analysed in a multilevel framework. Important statistical concepts, such as sampling and outliers, are covered specifically for multilevel data. Repeated measures, outliers, institutional performance, and spatial analysis, which have great relevance to health and medical research, are all examined for multilevel models. The book is aimed at health care professionals and public health researchers interested in the application of statistics, and will also be of interest to postgraduate students studying medical statistics. Wiley Series in Probability and Statistics

Multilevel Models
Multilevel Models

Author: Jichuan Wang

Publisher: Walter de Gruyter

Published: 2011-12-23

Total Pages: 275

ISBN-13: 3110267705

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Interest in multilevel statistical models for social science and public health studies has been aroused dramatically since the mid-1980s. New multilevel modeling techniques are giving researchers tools for analyzing data that have a hierarchical or clustered structure. Multilevel models are now applied to a wide range of studies in sociology, population studies, education studies, psychology, economics, epidemiology, and public health. This book covers a broad range of topics about multilevel modeling. The goal of the authors is to help students and researchers who are interested in analysis of multilevel data to understand the basic concepts, theoretical frameworks and application methods of multilevel modeling. The book is written in non-mathematical terms, focusing on the methods and application of various multilevel models, using the internationally widely used statistical software, the Statistics Analysis System (SAS®). Examples are drawn from analysis of real-world research data. The authors focus on twolevel models in this book because it is most frequently encountered situation in real research. These models can be readily expanded to models with three or more levels when applicable. A wide range of linear and non-linear multilevel models are introduced and demonstrated.

The Science of Health Disparities Research
The Science of Health Disparities Research

Author: Irene Dankwa-Mullan

Publisher: John Wiley & Sons

Published: 2021-03-16

Total Pages: 548

ISBN-13: 1119374812

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Integrates the various disciplines of the science of health disparities in one comprehensive volume The Science of Health Disparities Research is an indispensable source of up-to-date information on clinical and translational health disparities science. Building upon the advances in health disparities research over the past decade, this authoritative volume informs policies and practices addressing the diseases, disorders, and gaps in health outcomes that are more prevalent in minority populations and socially disadvantaged communities. Contributions by recognized scholars and leaders in the field—featuring contemporary research, conceptual models, and a broad range of scientific perspectives—provide an interdisciplinary approach to reducing inequalities in population health, encouraging community engagement in the research process, and promoting social justice. In-depth chapters help readers better understand the specifics of minority health and health disparities while demonstrating the importance of advancing theory, refining measurement, improving investigative methods, and diversifying scientific research. In 26 chapters, the book examines topics including the etiology of health disparities research, the determinants of population health, research ethics, and research in African American, Asians, Latino, American Indian, and other vulnerable populations. Providing a unified framework on the principles and applications of the science of health disparities research, this important volume: Defines the field of health disparities science and suggests new directions in scholarship and research Explains basic definitions, principles, and concepts for identifying, understanding and addressing health disparities Provides guidance on both conducting health disparities research and translating the results Examines how social, historical and contemporary injustices may influence the health of racial and ethnic minorities Illustrates the increasing national and global importance of addressing health disparities Discusses population health training, capacity-building, and the transdisciplinary tools needed to advance health equity A significant contribution to the field, The Science of Health Disparities Research is an essential resource for students and basic and clinical researchers in genetics, population genetics, and public health, health care policymakers, and epidemiologists, medical students, and clinicians, particularly those working with minority, vulnerable, or underserved populations.

Multilevel Modelling for Public Health and Health Services Research
Multilevel Modelling for Public Health and Health Services Research

Author: Alastair H. Leyland

Publisher: Springer Nature

Published: 2020-02-28

Total Pages: 293

ISBN-13: 3030348016

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This open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) – a statistical technique being increasingly used in public health and health services research. The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the growing body of research that uses it, but also to recognise the limitations of research that did not use it. The volume also guides the analysis of real-life data sets by introducing and discussing the use of the multilevel modelling software MLwiN, the statistical package that is used with the example data sets. Importantly, the book also makes the training material accessible for download – not only the datasets analysed within the book, but also a freeware version of MLwiN to allow readers to work with these datasets. The book’s practical review of MLA comprises: Theoretical, conceptual, and methodological background Statistical background The modelling process and presentation of research Tutorials with example datasets Multilevel Modelling for Public Health and Health Services Research: Health in Context is a practical and timely resource for public health and health services researchers, statisticians interested in the relationships between contexts and behaviour, graduate students across these disciplines, and anyone interested in utilising multilevel modelling or multilevel analysis. “Leyland and Groenewegen’s wealth of teaching experience makes this book and its accompanying tutorials especially useful for a practical introduction to multilevel analysis.” ̶ Juan Merlo, Professor of Social Epidemiology, Lund University “Comprehensive and insightful. A must for anyone interested in the applications of multilevel modelling to population health”. ̶ S. (Subu) V. Subramanian, Professor of Population Health and Geography, Harvard University

Applied Multilevel Analysis
Applied Multilevel Analysis

Author: Jos W. R. Twisk

Publisher: Cambridge University Press

Published: 2006-03-28

Total Pages: 196

ISBN-13: 9780521614986

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This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians; those books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the practical application of multilevel analysis in research. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyze the data. This approach will help bridge the conceptual and communication gap that exists between researchers and statisticians.

The Future of the Public's Health in the 21st Century
The Future of the Public's Health in the 21st Century

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2003-02-01

Total Pages: 536

ISBN-13: 0309133181

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The anthrax incidents following the 9/11 terrorist attacks put the spotlight on the nation's public health agencies, placing it under an unprecedented scrutiny that added new dimensions to the complex issues considered in this report. The Future of the Public's Health in the 21st Century reaffirms the vision of Healthy People 2010, and outlines a systems approach to assuring the nation's health in practice, research, and policy. This approach focuses on joining the unique resources and perspectives of diverse sectors and entities and challenges these groups to work in a concerted, strategic way to promote and protect the public's health. Focusing on diverse partnerships as the framework for public health, the book discusses: The need for a shift from an individual to a population-based approach in practice, research, policy, and community engagement. The status of the governmental public health infrastructure and what needs to be improved, including its interface with the health care delivery system. The roles nongovernment actors, such as academia, business, local communities and the media can play in creating a healthy nation. Providing an accessible analysis, this book will be important to public health policy-makers and practitioners, business and community leaders, health advocates, educators and journalists.

Oxford Textbook of Global Public Health
Oxford Textbook of Global Public Health

Author: Roger Detels

Publisher: Oxford University Press

Published: 2017

Total Pages: 1717

ISBN-13: 019881013X

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Sixth edition of the hugely successful, internationally recognised textbook on global public health and epidemiology, with 3 volumes comprehensively covering the scope, methods, and practice of the discipline

Multilevel Analysis
Multilevel Analysis

Author: Joop J. Hox

Publisher: Routledge

Published: 2010-09-13

Total Pages: 564

ISBN-13: 1136975349

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This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions, making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models. Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8). Thoroughly updated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years. The addition of some simpler examples to help the novice, whilst the more complex examples that combine more than one problem have been retained. A new section on multivariate meta-analysis (Ch. 11). Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected. Expanded chapter on the logistic model for dichotomous data and proportions with new estimation methods. An updated website at http://www.joophox.net/ with data sets for all the text examples and up-to-date screen shots and PowerPoint slides for instructors. Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including: psychology, education, sociology, the health sciences, and business. The advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.