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Regression Methods in Biostatistics

Linear, Logistic, Survival, and Repeated Measures Models
Buch | Hardcover
509 Seiten
2011 | 2nd ed. 2012
Springer-Verlag New York Inc.
978-1-4614-1352-3 (ISBN)

Lese- und Medienproben

Regression Methods in Biostatistics - Eric Vittinghoff, David V. Glidden, Stephen C. Shiboski, Charles E. McCulloch
CHF 164,75 inkl. MwSt
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.
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.

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).

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.

Reihe/Serie Statistics for Biology and Health
Zusatzinfo XX, 509 p.
Verlagsort New York, NY
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Studium Querschnittsbereiche Epidemiologie / Med. Biometrie
Studium Querschnittsbereiche Prävention / Gesundheitsförderung
Naturwissenschaften Biologie
Sozialwissenschaften Pädagogik
Sozialwissenschaften Soziologie
Schlagworte applied regression methods for biomedical research • confounding, mediation, and interaction • linear, logistic, generalized linear, survival (Cox), GEE, a • model selection and checking • statistical computing with STATA
ISBN-10 1-4614-1352-4 / 1461413524
ISBN-13 978-1-4614-1352-3 / 9781461413523
Zustand Neuware
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