Regression Models as a Tool in Medical Research

Author: Werner Vach
Edition: 1
Publisher: Chapman and Hall/CRC
Binding: Hardcover
ISBN: 1466517484

Regression Models as a Tool in Medical Research

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. Medical books Regression Models as a Tool in Medical Research. 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 Medical books Regression Models As A Tool In Medical Research By Werner Vach Hardcover Boo. Store Search search Title, ISBN and Author Regression Models as a Tool in Medical Research by Werner Vach Estimated delivery 4-14 business days Format Hardcover Condition Brand New Details ISBN 1466517484 ISBN-13 9781466517486 Title Regression Models as a Tool in Medical Research Author Werner Vach Format Hardcover Year 2012 Pages 473 Publisher CRC Press Dimensions 6.2 in. x 1.3 in. x 9.2 in. About Us Grand Eagle Retail is the ideal place for all your reading and entertainment needs! With fast

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Store Search search Title, ISBN and Author Regression Models as a Tool in Medical Research by Werner Vach Estimated delivery 4-14 business days Format Hardcover Condition Brand New Details ISBN 1466517484 ISBN-13 9781466517486 Title Regression Models as a Tool in Medical Research Author Werner Vach Format Hardcover Year 2012 Pages 473 Publisher CRC Press Dimensions 6.2 in. x 1.3 in. x 9.2 in. About Us Grand Eagle Retail is the ideal place for all your reading and entertainment needs! With fast

Regression Models As A Tool In Medical Research

While Regression models have become standard tools in Medical research, understanding how to propTHE BASICSWhy Use Regression Models?Why using simple regression models?Why using multiple regression models?Some basic notationAn Introductory ExampleA single line modelFi

"Preface Regression models are today a standard tool in medical research. However, their application and the interpretation of their results is often challenging. It is the purpose of this book to introduce medical researchers to basic concepts and other important aspects of regression models, which have to be taken into account in their application to ensure an optimal use and in the interpretation of their results to support the adequate addressing of subject matter questions. Three regression models are in particular popular in medical research: The classical regression model for a continuo

Medical Book Regression Models as a Tool in Medical Research

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.