This new book provides a unified, in-depth, 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 right-censored survival times,
repeated-measures 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 many-shared 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. For many students and researchers
learning to use these methods, this one book may be all they need to
conduct and interpret multipredictor regression analyses. The authors
are on the faculty in the Division of Biostatistics, Department of
Epidemiology and Biostatistics, University of California, San
Francisco, and are authors or co-authors of more than 200
methodological as well as applied papers in the biological and
biomedical sciences. The senior author, Charles E. McCulloch, is head
of the Division and author of Generalized Linear Mixed Models (2003),
Generalized, Linear, and Mixed Models (2000), and Variance Components
(1992). From the reviews: "This book provides a unified introduction
to the regression methods listed in the title...The methods are well
illustrated by data drawn from medical studies...A real strength of
this book is the careful discussion of issues common to all of the
multipredictor methods covered." Journal of Biopharmaceutical
Statistics, 2005 "This book is not just for biostatisticians. It is,
in fact, a very good, and relatively nonmathematical, overview of
multipredictor regression models. Although the examples are
biologically oriented, they are generally easy to understand and
follow...I heartily recommend the book" Technometrics, February 2006
"Overall, the text provides an overview of regression methods that is
particularly strong in its breadth of coverage and emphasis on insight
in place of mathematical detail. As intended, this well-unified
approach should appeal to students who learn conceptually and
verbally." Journal of the American Statistical Association, March 2006
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Produktdetaljer
ISBN
9781461413530
Publisert
2018
Utgave
2. utgave
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok