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Regression Methods in Biostatistics - David V. Glidden; Charles E. McCulloch; Stephen C. Shiboski; Eric Vittinghoff
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David V. Glidden; Charles E. McCulloch; Stephen C. Shiboski; Eric Vittinghoff:

Regression Methods in Biostatistics - neues Buch

2012, ISBN: 9781461413530

Linear, Logistic, Survival, and Repeated Measures Models, eBooks, eBook Download (PDF), 2nd ed. 2012, This new book provides a unified, in-depth, readable introduction to the multipredict… Mehr…

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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models - David A. Papa
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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models - neues Buch

2006, ISBN: 9781461413530

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, logist… Mehr…

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Regression Methods in Biostatistics - Eric Vittinghoff/ David V. Glidden/ Stephen C. Shiboski/ Charles E. McCulloch
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Eric Vittinghoff/ David V. Glidden/ Stephen C. Shiboski/ Charles E. McCulloch:
Regression Methods in Biostatistics - neues Buch

ISBN: 9781461413530

*Regression Methods in Biostatistics* - Linear Logistic Survival and Repeated Measures Models / pdf eBook für 96.49 € / Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Medizin Medien … Mehr…

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Regression Methods in Biostatistics - Eric Vittinghoff/ David V. Glidden/ Stephen C. Shiboski/ Charles E. McCulloch
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Eric Vittinghoff/ David V. Glidden/ Stephen C. Shiboski/ Charles E. McCulloch:
Regression Methods in Biostatistics - neues Buch

ISBN: 9781461413530

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Regression Methods in Biostatistics - Eric Vittinghoff; David V. Glidden; Stephen C. Shiboski; Charles E. McCulloch
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Eric Vittinghoff; David V. Glidden; Stephen C. Shiboski; Charles E. McCulloch:
Regression Methods in Biostatistics - neues Buch

2012, ISBN: 9781461413530

Linear, Logistic, Survival, and Repeated Measures Models, eBooks, eBook Download (PDF), Auflage, [PU: Springer-Verlag], [ED: 2], Springer-Verlag, 2012

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Bibliographische Daten des bestpassenden Buches

Details zum Buch

Detailangaben zum Buch - Regression Methods in Biostatistics


EAN (ISBN-13): 9781461413530
ISBN (ISBN-10): 1461413532
Erscheinungsjahr: 2012
Herausgeber: Springer-Verlag GmbH
509 Seiten
Sprache: eng/Englisch

Buch in der Datenbank seit 2012-09-19T19:52:26+02:00 (Berlin)
Detailseite zuletzt geändert am 2023-10-22T20:17:21+02:00 (Berlin)
ISBN/EAN: 9781461413530

ISBN - alternative Schreibweisen:
1-4614-1353-2, 978-1-4614-1353-0
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: vittinghoff, mcculloch, char, charles glidden


Daten vom Verlag:

Autor/in: Eric Vittinghoff; David V. Glidden; Stephen C. Shiboski; Charles E. McCulloch
Titel: Statistics for Biology and Health; Regression Methods in Biostatistics - Linear, Logistic, Survival, and Repeated Measures Models
Verlag: Springer; Springer US
509 Seiten
Erscheinungsjahr: 2012-03-06
New York; NY; US
Gedruckt / Hergestellt in Großbritannien.
Sprache: Englisch
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XX, 512 p.

EA; E107; eBook; Nonbooks, PBS / Medizin/Allgemeines; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; adopted-textbook; 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; B; Statistics for Life Sciences, Medicine, Health Sciences; Epidemiology; Public Health; Biostatistics; Epidemiology; Public Health; Mathematics and Statistics; Epidemiologie und medizinische Statistik; Public Health und Präventivmedizin; BB

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.

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:

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.

Short and to the point so that the important issues and similarities between the methods, rather than the differences, shine through

Provides a unified introduction to the regression methods listed in the title

Unified approach should appeal to students who learn conceptually and verbally

Includes supplementary material: sn.pub/extras


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.

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