Regression methods in biostatistics : linear, logistic, survival, and repeated measures models
 Responsibility
 Eric Vittinghoff ... [et al.].
 Language
 English.
 Edition
 2nd ed.
 Imprint
 New York : Springer, c2012.
 Physical description
 xx, 509 p. : ill. ; 25 cm.
 Series
 Statistics for biology and health.
Access
Available online
Course reserve
 Course
 STATS26201  Intermediate Biostatistics: Regression, Prediction. Survival
 Instructor(s)
 Sainani, Kristin Lynn
Math & Statistics Library
On reserve: Ask at circulation desk
Call number  Status 

QH323.5 .R43 2012  1day loan 
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Creators/Contributors
 Contributor
 Vittinghoff, Eric.
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 489500) and index.
 Contents

 Introduction. Exploratory and Descriptive Methods. Basic Statistical Methods. Linear Regression. Logistic Regression. Survival Analysis. Repeated Measures Analysis. Generalized Linear Models. Strengthening Casual Inference. Predictor Selection. Complex Surveys. Summary.
 (source: Nielsen Book Data)
 Publisher's Summary
 This new book provides a unified, indepth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for rightcensored survival times, repeatedmeasures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the manyshared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
(source: Nielsen Book Data)
Subjects
Bibliographic information
 Publication date
 2012
 Series
 Statistics for biology and health, 14318776
 ISBN
 9781461413523 (alk. paper)
 1461413524 (alk. paper)
 9781461413530 (eISBN)