Association Models In Epidemiology
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Association Models In Epidemiology
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Author : Hongjie Liu
language : en
Publisher: CRC Press
Release Date : 2024-08-05
Association Models In Epidemiology written by Hongjie Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-05 with Medical categories.
Association Models in Epidemiology: Study Designs, Modeling Strategies, and Analytic Methods is written by an epidemiologist for graduate students, researchers, and practitioners who will use regression techniques to analyze data. It focuses on association models rather than prediction models. The book targets students and working professionals who lack bona fide modeling experts but are committed to conducting appropriate regression analyses and generating valid findings from their projects. This book aims to offer detailed strategies to guide them in modeling epidemiologic data. Features Custom-Tailored Models: Discover association models specifically designed for epidemiologic study designs. Epidemiologic Principles in Action: Learn how to apply and translate epidemiologic principles into regression modeling techniques. Model Specification Guidance: Get expert guidance on model specifications to estimate exposure-outcome associations, accurately controlling for confounding bias. Accessible Language: Explore regression intricacies in user-friendly language, accompanied by real-world examples that make learning easier. Step-by-Step Approach: Follow a straightforward step-by-step approach to master strategies and procedures for analysis. Rich in Examples: Benefit from 120 examples, 77 figures, 86 tables, and 174 SAS® outputs with annotations to enhance your understanding. Book website located here. Crafted for two primary audiences, this text benefits graduate epidemiology students seeking to understand how epidemiologic principles inform modeling analyses and public health professionals conducting independent analyses in their work. Therefore, this book serves as a textbook in the classroom and as a reference book in the workplace. A wealth of supporting material is available for download from the book’s CRC Press webpage. Upon completing this text, readers should gain confidence in accurately estimating associations between risk factors and outcomes, controlling confounding bias, and assessing effect modification.
Association Models In Epidemiology
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Author : Hongjie Liu
language : en
Publisher:
Release Date : 2025
Association Models In Epidemiology written by Hongjie Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
"Association Models in Epidemiology: Study Design, Modeling Strategies, and Analytic Methods provides detailed strategies in modeling analyses of epidemiologic data. It focuses on integrating epidemiologic principles with statistical modeling methods in such a way that the principles inform the choice of modeling strategy and covariate selection. Specific statistical models are tailored to analyze data collected from different epidemiologic study designs, i.e., data analysis by study design. The study designs highlighted in this book include cross-sectional, case-control, and cohort studies. The analytic strategies covered emphasize model specification, effect estimation, control of confounding, and assessment of modification and mediation effects. Detailed modeling techniques include logistic regression, conditional logistic regression, log-binomial regression, Cox proportional hazards, Poisson regression, negative binomial regression, path analytic model, and propensity-score analysis. Features: Modeling of epidemiologic data by study design Integration of epidemiologic principles with biostatistics Development of analytic strategies for each study design Use of the directed acyclic graph (DAG) in model specification Modelling assumptions and alternatives Step-by-step modeling approach using SAS® software Exercises in each chapter to enable use as a course text or for self-study The textbook is primarily aimed at graduate students in epidemiology taking a course on advanced methods in epidemiology. It has been developed from a course taught by the author for many years at the University of Maryland, but it could also be used for self-study. It will also be useful as a reference for epidemiologists who need to perform valid and accurate analyses independently as part of their jobs"--
Applications Of Regression Models In Epidemiology
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Author : Erick Suárez
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-28
Applications Of Regression Models In Epidemiology written by Erick Suárez and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-28 with Mathematics categories.
A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: • Is based on the authors’ course notes from 20 years teaching regression modeling in public health courses • Provides exercises at the end of each chapter • Contains a solutions chapter with answers in STATA, SAS, SPSS, and R • Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of Regression Models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SUÁREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. He received a Ph.D. degree in Medical Statistics from the London School of Hygiene and Tropical Medicine. He has 29 years of experience teaching biostatistics. CYNTHIA M. PÉREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. She received an M.S. degree in Statistics and a Ph.D. degree in Epidemiology from Purdue University. She has 22 years of experience teaching epidemiology and biostatistics. ROBERTO RIVERA is an Associate Professor at the College of Business at the University of Puerto Rico at Mayaguez. He received a Ph.D. degree in Statistics from the University of California in Santa Barbara. He has more than five years of experience teaching statistics courses at the undergraduate and graduate levels. MELISSA N. MARTÍNEZ is an Account Supervisor at Havas Media International. She holds an MPH in Biostatistics from the University of Puerto Rico and an MSBA from the National University in San Diego, California. For the past seven years, she has been performing analyses for the biomedical research and media advertising fields.
Analysis Of Cancer Risks In Populations Near Nuclear Facilities
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2012-06-29
Analysis Of Cancer Risks In Populations Near Nuclear Facilities written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-29 with Medical categories.
In the late 1980s, the National Cancer Institute initiated an investigation of cancer risks in populations near 52 commercial nuclear power plants and 10 Department of Energy nuclear facilities (including research and nuclear weapons production facilities and one reprocessing plant) in the United States. The results of the NCI investigation were used a primary resource for communicating with the public about the cancer risks near the nuclear facilities. However, this study is now over 20 years old. The U.S. Nuclear Regulatory Commission requested that the National Academy of Sciences provide an updated assessment of cancer risks in populations near USNRC-licensed nuclear facilities that utilize or process uranium for the production of electricity. Analysis of Cancer Risks in Populations near Nuclear Facilities: Phase 1 focuses on identifying scientifically sound approaches for carrying out an assessment of cancer risks associated with living near a nuclear facility, judgments about the strengths and weaknesses of various statistical power, ability to assess potential confounding factors, possible biases, and required effort. The results from this Phase 1 study will be used to inform the design of cancer risk assessment, which will be carried out in Phase 2. This report is beneficial for the general public, communities near nuclear facilities, stakeholders, healthcare providers, policy makers, state and local officials, community leaders, and the media.
Epidemics
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Author : Ottar N. Bjørnstad
language : en
Publisher: Springer
Release Date : 2018-11-08
Epidemics written by Ottar N. Bjørnstad and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-08 with Medical categories.
This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in ‘consumer-resource metapopulations’. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and ‘models-with-data’ have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data using R have been organized in a reasonably logical way: Chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; Chapters 11-13 pertains to spatial and spatiotemporal dynamics; Chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, Chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and ‘models-and-data’ to understand epidemics and infectious disease dynamics in space and time.
Statistical Models In Epidemiology
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Author : David Clayton
language : en
Publisher: Oxford University Press (UK)
Release Date : 2013-01-17
Statistical Models In Epidemiology written by David Clayton and has been published by Oxford University Press (UK) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-17 with Mathematics categories.
This self-contained account of the statistical basis of epidemiology has been written for those with a basic training in biology. It is specifically intended for students enrolled for a masters degree in epidemiology, clinical epidemiology, or biostatistics.
Basic Epidemiology
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Author : R. Bonita
language : en
Publisher: World Health Organization
Release Date : 2006
Basic Epidemiology written by R. Bonita and has been published by World Health Organization this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Medical categories.
Basic epidemiology provides an introduction to the core principles and methods of epidemiology, with a special emphasis on public health applications in developing countries. This edition includes chapters on the nature and uses of epidemiology; the epidemiological approach to defining and measuring the occurrence of health-related states in populations; the strengths and limitations of epidemiological study designs; and the role of epidemiology in evaluating the effectiveness and efficiency of health care. The book has a particular emphasis on modifiable environmental factors and encourages the application of epidemiology to the prevention of disease and the promotion of health, including environmental and occupational health.
Epidemiology
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Author : Mark Woodward
language : en
Publisher: CRC Press
Release Date : 2013-12-19
Epidemiology written by Mark Woodward and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-19 with Mathematics categories.
Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems. New to the Third Edition New chapter on risk scores and clinical decision rules New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines Many more exercises and examples using both Stata and SAS More than 60 new figures After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding. Web Resource A wealth of supporting material can be downloaded from the book’s CRC Press web page, including: Real-life data sets used in the text SAS and Stata programs used for examples in the text SAS and Stata programs for special techniques covered Sample size spreadsheet
Applied Bayesian Modeling And Causal Inference From Incomplete Data Perspectives
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Author : Andrew Gelman
language : en
Publisher: John Wiley & Sons
Release Date : 2004-10-22
Applied Bayesian Modeling And Causal Inference From Incomplete Data Perspectives written by Andrew Gelman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-10-22 with Mathematics categories.
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.
Genetic Association Studies Background Conduct Analysis Interpretation
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Author : Mehmet Tevfik Dorak
language : en
Publisher: Garland Science
Release Date : 2016-09-28
Genetic Association Studies Background Conduct Analysis Interpretation written by Mehmet Tevfik Dorak and has been published by Garland Science this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-28 with Science categories.
Genetic Association Studies is designed for students of public health, epidemiology, and the health sciecnes, covering the main principles of molecular genetics, population genetics, medical genetics, epidemiology and statistics. It presents a balanced view of genetic associations with coverage of candidate gene studies as well as genome-wide association studies. All aspects of a genetic association study are included, from the lab to analysis and interpretation of results, but also bioinformatics approaches to causality assessment. The role of the environment in genetic disease is also highlighted. Genetic Association Studies will enable readers to understand and critique genetic association studies and set them on the way to designing, executing, analyzing, interpreting, and reporting their own.