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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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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 - neues Buch2006, 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…
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…
ISBN: 9781461413530
Regression Methods in Biostatistics - Linear Logistic Survival and Repeated Measures Models: ab 96.49 € eBooks > Fachthemen & Wissenschaft > Medizin Springer-Verlag GmbH eBook als pdf, Sp… Mehr…
2012, ISBN: 9781461413530
Linear, Logistic, Survival, and Repeated Measures Models, eBooks, eBook Download (PDF), Auflage, [PU: Springer-Verlag], [ED: 2], Springer-Verlag, 2012
Bibliographische Daten des bestpassenden Buches
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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
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
Sprache: Englisch
99,00 € (DE)
EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; 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; Biostatistics; Epidemiology; Public Health; Mathematics and Statistics; Epidemiologie und medizinische Statistik; Public Health und Präventivmedizin; BB
This new edition 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. In the second edition, the authors have substantially expanded the core chapters, including new coverage of exact, ordinal, and multinomial logistic models, discrete time and competing risks survival models, within and between effects in longitudinal models, zero-inflated Poisson and negative binomial models, cross-validation for prediction model selection, directed acyclic graphs, and sample size, power and minimum detectable effect calculations; Stata code is also updated. In addition, there are new chapters on methods for strengthening causal inference, including propensity scores, marginal structural models, and instrumental variables, and on methods for handling missing data, using maximum likelihood, multiple imputation, inverse weighting, and pattern mixture models.From the reviews of the first edition: "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 2006Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
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