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Multivariate Methods in Epidemiology

Multivariate Methods in Epidemiology
Author: Theodore R. Holford
Publisher: Oxford University Press
Total Pages: 427
Release: 2002-05-30
Genre: Medical
ISBN: 0199747768
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The basis for much of medical public health practice comes from epidemiological research. This text describes current statistical tools that are used to analyze the association between possible risk factors and the actual risk of disease. Beginning with a broad conceptual framework on the disease process, it describes commonly used techniques for analyzing proportions and disease rates. These are then extended to model fitting, and the common threads of logic that bind the two analytic strategies together are revealed. Each chapter provides a descriptive rationale for the method, a worked example using data from a published study, and an exercise that allows the reader to practice the technique. Each chapter also includes an appendix that provides further details on the theoretical underpinnings of the method. Among the topics covered are Mantel-Haenszel methods, rates, survival analysis, logistic regression, and generalized linear models. Methods for incorporating aspects of study design, such as matching, into the analysis are discussed, and guidance is given for determining the power or the sample size requirements of a study. This text will give readers a foundation in applied statistics and the concepts of model fitting to develop skills in the analysis of epidemiological data.

Practical Multivariate Analysis

Practical Multivariate Analysis
Author: Abdelmonem Afifi
Publisher: CRC Press
Total Pages: 528
Release: 2019-10-16
Genre: Mathematics
ISBN: 1351788906
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This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.

Multivariate Statistics

Multivariate Statistics
Author: Bernhard Flury
Publisher: Springer
Total Pages: 314
Release: 2011-09-20
Genre: Science
ISBN: 9789401070416
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During the last twenty years multivariate statistical methods have become increasingly popular among scientists in various fields. The theory had already made great progress in previous decades and routine applications of multivariate methods followed with the advent of fast computers. Nowadays statistical software packages perform in seconds what used to take weeks of tedious calculations. Although this is certainly a welcome development, we find, on the other hand, that many users of statistical packages are not too sure of what they are doing, and this is especially true for multivariate statistical methods. Many researchers have heard about such techniques and feel intuitively that multivariate methods could be useful for their own work, but they haven't mastered the usual mathematical prerequisites. This book tries to fill the gap by explaining - in words and graphs - some basic concepts and selected methods of multivariate statistical analysis. Why another book? Are the existing books on applied multivariate statistics all obsolete? No, some of them are up to date and, indeed, quite good.

Applied Multivariate Statistics with R

Applied Multivariate Statistics with R
Author: Daniel Zelterman
Publisher: Springer Nature
Total Pages: 469
Release: 2023-01-20
Genre: Medical
ISBN: 3031130057
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Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.

Multivariable Analysis

Multivariable Analysis
Author: Mitchell H. Katz
Publisher: Cambridge University Press
Total Pages: 228
Release: 2006-02-09
Genre: Medical
ISBN: 9780521549851
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How to perform and interpret multivariable analysis, using plain language rather than complex derivations.

Approaching Multivariate Analysis, 2nd Edition

Approaching Multivariate Analysis, 2nd Edition
Author: Pat Dugard
Publisher: Taylor & Francis
Total Pages: 440
Release: 2022-06-30
Genre: Psychology
ISBN: 1000787257
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This fully updated new edition not only provides an introduction to a range of advanced statistical techniques that are used in psychology, but has been expanded to include new chapters describing methods and examples of particular interest to medical researchers. It takes a very practical approach, aimed at enabling readers to begin using the methods to tackle their own problems. This book provides a non-mathematical introduction to multivariate methods, with an emphasis on helping the reader gain an intuitive understanding of what each method is for, what it does and how it does it. The first chapter briefly reviews the main concepts of univariate and bivariate methods and provides an overview of the multivariate methods that will be discussed, bringing out the relationships among them, and summarising how to recognise what types of problem each of them may be appropriate for tackling. In the remaining chapters, introductions to the methods and important conceptual points are followed by the presentation of typical applications from psychology and medicine, using examples with fabricated data. Instructions on how to do the analyses and how to make sense of the results are fully illustrated with dialogue boxes and output tables from SPSS, as well as details of how to interpret and report the output, and extracts of SPSS syntax and code from relevant SAS procedures. This book gets students started, and prepares them to approach more comprehensive treatments with confidence. This makes it an ideal text for psychology students, medical students and students or academics in any discipline that uses multivariate methods.

Statistics in Epidemiology

Statistics in Epidemiology
Author: Hardeo Sahai
Publisher: CRC Press
Total Pages: 350
Release: 1995-12-21
Genre: Mathematics
ISBN: 9780849394447
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Epidemiologic studies provide research strategies for investigating public health and scientific questions relating to the factors that cause and prevent ailments in human populations. Statistics in Epidemiology: Methods, Techniques and Applications presents a comprehensive review of the wide range of principles, methods and techniques underlying prospective, retrospective and cross-sectional approaches to epidemiologic studies. Written for epidemiologists and other researchers without extensive backgrounds in statistics, this new book provides a clear and concise description of the statistical tools used in epidemiology. Emphasis is given to the application of these statistical tools, and examples are provided to illustrate direct methods for applying common statistical techniques in order to obtain solutions to problems. Statistics in Epidemiology: Methods, Techniques and Applications goes beyond the elementary material found in basic epidemiology and biostatistics books and provides a detailed account of techniques:

Modern Methods for Epidemiology

Modern Methods for Epidemiology
Author: Yu-Kang Tu
Publisher: Springer Science & Business Media
Total Pages: 315
Release: 2012-05-22
Genre: Medical
ISBN: 9400730241
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Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.

Biostatistics for Epidemiologists

Biostatistics for Epidemiologists
Author: Anders Ahlbom
Publisher: CRC Press
Total Pages: 133
Release: 2017-11-22
Genre: Medical
ISBN: 1351463667
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Biostatistics for Epidemiologists is a unique book that provides a collection of methods that can be used to analyze data in most epidemiological studies. It examines the theoretical background of the methods described and discusses general principles that apply to the analysis of epidemiological data. Specific topics addressed include statistical interference in epidemiological research, important methods used for analyzing epidemiological data, multivariate models, dose-response analysis, analysis of the interaction between causes of disease, meta-analysis, and computer programs. Biostatistics for Epidemiologists will be a useful guide for all epidemiologists and public health professionals who rely on biostatistical data in their work.

Statistical Approaches for Epidemiology

Statistical Approaches for Epidemiology
Author: Amal K. Mitra
Publisher: Springer Nature
Total Pages: 445
Release: 2023-12-12
Genre: Medical
ISBN: 3031417844
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This textbook provides the basic concepts of epidemiology while preparing readers with the skills of applying statistical tools in real-life situations. Students, in general, struggle with statistical theories and their practical applications. This book makes statistical concepts easy to understand by focusing on real-life examples, case studies, and exercises. It also provides step-by-step guides for data analysis and interpretation using standard statistical software such as SPSS, SAS, R, Python, and GIS as appropriate, illustrating the concepts. Through the book's 23 chapters, readers primarily learn how to apply statistical methods in epidemiological studies and problem-solving. Among the topics covered: Clinical Trials Epidemic Investigation and Control Geospatial Applications in Epidemiology Survival Analysis and Applications Using SAS and SPSS Systematic Review and Meta-Analysis: Evidence-based Decision-Making in Public Health Missing Data Imputation: A Practical Guide Artificial Intelligence and Machine Learning Multivariate Linear Regression and Logistics Regression Analysis Using SAS Each chapter is written by eminent scientists and experts worldwide, including contributors from institutions in the United States, Canada, Bangladesh, India, Hong Kong, Malaysia, and the Middle East. Statistical Approaches for Epidemiology: From Concept to Application is an all-in-one book that serves as an essential text for graduate students, faculty, instructors, and researchers in public health and other branches of health sciences, as well as a useful resource for health researchers in industry, public health and health department professionals, health practitioners, and health research organizations and non-governmental organizations. The book also will be helpful for graduate students and faculty in related disciplines such as data science, nursing, social work, environmental health, occupational health, computer science, statistics, and biology.