Applications of Regression Models in Epidemiology

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Publisher : John Wiley & Sons
ISBN 13 : 1119212502
Total Pages : 272 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Applications of Regression Models in Epidemiology by : Erick Suárez

Download or read book Applications of Regression Models in Epidemiology written by Erick Suárez and published by John Wiley & Sons. This book was released on 2017-02-13 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applied Survival Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 1118211588
Total Pages : 285 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Applied Survival Analysis by : David W. Hosmer, Jr.

Download or read book Applied Survival Analysis written by David W. Hosmer, Jr. and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.

Regression Modeling with Actuarial and Financial Applications

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Author :
Publisher : Cambridge University Press
ISBN 13 : 0521760119
Total Pages : 585 pages
Book Rating : 4.5/5 (217 download)

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Book Synopsis Regression Modeling with Actuarial and Financial Applications by : Edward W. Frees

Download or read book Regression Modeling with Actuarial and Financial Applications written by Edward W. Frees and published by Cambridge University Press. This book was released on 2010 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.

Regression Models as a Tool in Medical Research

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Publisher : CRC Press
ISBN 13 : 1466517484
Total Pages : 497 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Regression Models as a Tool in Medical Research by : Werner Vach

Download or read book Regression Models as a Tool in Medical Research written by Werner Vach and published by CRC Press. This book was released on 2012-11-27 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct interpretation of results, appropriate presentation of results, and avoidance of potential pitfalls. After reviewing popular models and basic methods, the book focuses on advanced topics and techniques. It considers the comparison of regression coefficients, the selection of covariates, the modeling of nonlinear and nonadditive effects, and the analysis of clustered and longitudinal data, highlighting the impact of selection mechanisms, measurement error, and incomplete covariate data. The text then covers the use of regression models to construct risk scores and predictors. It also gives an overview of more specific regression models and their applications as well as alternatives to regression modeling. The mathematical details underlying the estimation and inference techniques are provided in the appendices.

Regression Methods in Biostatistics

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Publisher : Springer Science & Business Media
ISBN 13 : 1461413524
Total Pages : 526 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Regression Methods in Biostatistics by : Eric Vittinghoff

Download or read book Regression Methods in Biostatistics written by Eric Vittinghoff and published by Springer Science & Business Media. This book was released on 2012 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.

Regression

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Publisher : Springer Science & Business Media
ISBN 13 : 3642343333
Total Pages : 768 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Regression by : Ludwig Fahrmeir

Download or read book Regression written by Ludwig Fahrmeir and published by Springer Science & Business Media. This book was released on 2013-05-09 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.

Exposure Assessment in Environmental Epidemiology

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Author :
Publisher : Oxford University Press, USA
ISBN 13 : 0199378789
Total Pages : 417 pages
Book Rating : 4.1/5 (993 download)

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Book Synopsis Exposure Assessment in Environmental Epidemiology by : Mark J. Nieuwenhuijsen

Download or read book Exposure Assessment in Environmental Epidemiology written by Mark J. Nieuwenhuijsen and published by Oxford University Press, USA. This book was released on 2015 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Preceded by Exposure assessment in occupational and environmental epidemiology / edited by Mark J. Nieuwenhuijsen. 1st ed. 2003.

The Cox Model and Its Applications

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Publisher : Springer
ISBN 13 : 3662493322
Total Pages : 124 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis The Cox Model and Its Applications by : Mikhail Nikulin

Download or read book The Cox Model and Its Applications written by Mikhail Nikulin and published by Springer. This book was released on 2016-04-11 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control. Since Sir David Cox’s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further studies in semiparametric and nonparametric theories, counting process models, study designs in epidemiology, and the development of many other regression models that could offer more flexible or more suitable approaches in data analysis. Flexible semiparametric regression models are increasingly being used to relate lifetime distributions to time-dependent explanatory variables. Throughout the book, various recent statistical models are developed in close connection with specific data from experimental studies in clinical trials or from observational studies.

Nonlinear Regression Analysis and Its Applications

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Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 398 pages
Book Rating : 4.:/5 (318 download)

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Book Synopsis Nonlinear Regression Analysis and Its Applications by : Douglas M. Bates

Download or read book Nonlinear Regression Analysis and Its Applications written by Douglas M. Bates and published by Wiley-Interscience. This book was released on 2007-04-23 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a presentation of the theoretical, practical, and computational aspects of nonlinear regression. There is background material on linear regression, including a geometrical development for linear and nonlinear least squares.

Regression Methods for Medical Research

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Publisher : John Wiley & Sons
ISBN 13 : 1118721985
Total Pages : 388 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Regression Methods for Medical Research by : Bee Choo Tai

Download or read book Regression Methods for Medical Research written by Bee Choo Tai and published by John Wiley & Sons. This book was released on 2013-10-09 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures. The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the key design questions posed and in so doing take due account of any effects of potentially influencing co-variables. It begins with a revision of basic statistical concepts, followed by a gentle introduction to the principles of statistical modelling. The various methods of modelling are covered in a non-technical manner so that the principles can be more easily applied in everyday practice. A chapter contrasting regression modelling with a regression tree approach is included. The emphasis is on the understanding and the application of concepts and methods. Data drawn from published studies are used to exemplify statistical concepts throughout. Regression Methods for Medical Research is especially designed for clinicians, public health and environmental health professionals, para-medical research professionals, scientists, laboratory-based researchers and students.

Medical Applications of Finite Mixture Models

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Publisher : Springer Science & Business Media
ISBN 13 : 3540686517
Total Pages : 252 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Medical Applications of Finite Mixture Models by : Peter Schlattmann

Download or read book Medical Applications of Finite Mixture Models written by Peter Schlattmann and published by Springer Science & Business Media. This book was released on 2009-03-02 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Patients are not alike! This simple truth is often ignored in the analysis of me- cal data, since most of the time results are presented for the “average” patient. As a result, potential variability between patients is ignored when presenting, e.g., the results of a multiple linear regression model. In medicine there are more and more attempts to individualize therapy; thus, from the author’s point of view biostatis- cians should support these efforts. Therefore, one of the tasks of the statistician is to identify heterogeneity of patients and, if possible, to explain part of it with known explanatory covariates. Finite mixture models may be used to aid this purpose. This book tries to show that there are a large range of applications. They include the analysis of gene - pression data, pharmacokinetics, toxicology, and the determinants of beta-carotene plasma levels. Other examples include disease clustering, data from psychophysi- ogy, and meta-analysis of published studies. The book is intended as a resource for those interested in applying these methods.

Statistics in Epidemiology

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Publisher : CRC Press
ISBN 13 : 9780849394447
Total Pages : 350 pages
Book Rating : 4.3/5 (944 download)

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Book Synopsis Statistics in Epidemiology by : Hardeo Sahai

Download or read book Statistics in Epidemiology written by Hardeo Sahai and published by CRC Press. This book was released on 1995-12-21 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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:

An Integrative Metaregression Framework for Descriptive Epidemiology

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Publisher :
ISBN 13 : 9780295991849
Total Pages : 0 pages
Book Rating : 4.9/5 (918 download)

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Book Synopsis An Integrative Metaregression Framework for Descriptive Epidemiology by : Abraham D. Flaxman

Download or read book An Integrative Metaregression Framework for Descriptive Epidemiology written by Abraham D. Flaxman and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: To provide the tools and knowledge needed in efforts to improve the health of the world's populations, researchers collaborated on the Global Burden of Diseases, Injuries, and Risk Factors Study 2010. The study produced comprehensive estimates of over 200 diseases and health risk factors in 187 countries over two decades, results that will be used by governments and non-governmental agencies to inform priorities for global health research, policies, and funding. Integrated Meta-Regression Framework for Descriptive Epidemiology is the first book-length treatment of model-based meta-analytic methods for descriptive epidemiology used in the Global Burden of Disease Study 2010. In addition to collecting the prior work on compartmental modeling of disease, this book significantly extends the model, by formally connecting the system dynamics model of disease progression to a statistical model of epidemiological rates and demonstrates how the two models were combined to allow researchers to integrate relevant data. Practical applications of the model to meta-analysis of more than a dozen different diseases complement the theoretical foundations of the integrative systems modeling of disease in populations. The book concludes with a detailed description of the future directions for research in model-based meta-analysis of descriptive epidemiological data. Abraham Flaxman is assistant professor of global health in the Institute for Health Metrics and Evaluation at the University of Washington.

Linear Models

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Publisher : Springer Science & Business Media
ISBN 13 : 0387227520
Total Pages : 429 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Linear Models by : Calyampudi R. Rao

Download or read book Linear Models written by Calyampudi R. Rao and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the theory and applications of linear models, for use as a textbook in statistics at graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models with minimal assumptions, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights include: - a special emphasis on sensitivity analysis and model selection; - a chapter devoted to the analysis of categorical data based on logic, loglinear, and logistic regression models; - a chapter devoted to incomplete data sets; - an extensive appendix on matrix theory; - a chapter devoted to the analysis of categorical data based on a unified presentation of generalized linear models including GEE-methods for correlated response; - a chapter devoted to incomplete data sets including regression diagnostics to identify Non-MCAR-processes The material covered is thus invaluable not only to graduates, but also to researchers and consultants in statistics.

Regression

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Publisher : Springer Nature
ISBN 13 : 3662638827
Total Pages : 759 pages
Book Rating : 4.6/5 (626 download)

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Book Synopsis Regression by : Ludwig Fahrmeir

Download or read book Regression written by Ludwig Fahrmeir and published by Springer Nature. This book was released on 2022-03-15 with total page 759 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book’s dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference. In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book. The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.

Statistical Approaches for Epidemiology

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Publisher : Springer Nature
ISBN 13 : 3031417844
Total Pages : 445 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Statistical Approaches for Epidemiology by : Amal K. Mitra

Download or read book Statistical Approaches for Epidemiology written by Amal K. Mitra and published by Springer Nature. This book was released on 2023-12-12 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Models in Epidemiology, the Environment, and Clinical Trials

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Publisher : Springer Science & Business Media
ISBN 13 : 9780387989242
Total Pages : 300 pages
Book Rating : 4.9/5 (892 download)

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Book Synopsis Statistical Models in Epidemiology, the Environment, and Clinical Trials by : M.Elizabeth Halloran

Download or read book Statistical Models in Epidemiology, the Environment, and Clinical Trials written by M.Elizabeth Halloran and published by Springer Science & Business Media. This book was released on 1999-10-29 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IMA Volume in Mathematics and its Applications STATISTICAL MODELS IN EPIDEMIOLOGY, THE ENVIRONMENT,AND CLINICAL TRIALS is a combined proceedings on "Design and Analysis of Clinical Trials" and "Statistics and Epidemiology: Environment and Health. " This volume is the third series based on the proceedings of a very successful 1997 IMA Summer Program on "Statistics in the Health Sciences. " I would like to thank the organizers: M. Elizabeth Halloran of Emory University (Biostatistics) and Donald A. Berry of Duke University (Insti tute of Statistics and Decision Sciences and Cancer Center Biostatistics) for their excellent work as organizers of the meeting and for editing the proceedings. I am grateful to Seymour Geisser of University of Minnesota (Statistics), Patricia Grambsch, University of Minnesota (Biostatistics); Joel Greenhouse, Carnegie Mellon University (Statistics); Nicholas Lange, Harvard Medical School (Brain Imaging Center, McLean Hospital); Barry Margolin, University of North Carolina-Chapel Hill (Biostatistics); Sandy Weisberg, University of Minnesota (Statistics); Scott Zeger, Johns Hop kins University (Biostatistics); and Marvin Zelen, Harvard School of Public Health (Biostatistics) for organizing the six weeks summer program. I also take this opportunity to thank the National Science Foundation (NSF) and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr.