Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data

Dupont, William D.

ISBN 10: 0521614805 / ISBN 13: 9780521614801

Verlag: Cambridge University Press, 2009

Beschreibung

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Bibliografische Details

Titel: Statistical Modeling for Biomedical ...

Verlag: Cambridge University Press

Erscheinungsdatum: 2009

Einband: Paperback

Zustand: Good

Auflage: 2. Auflage

Über diesen Titel

Inhaltsangabe:

The second edition of this standard text guides biomedical researchers in the selection and use of advanced statistical methods and the presentation of results to clinical colleagues. It assumes no knowledge of mathematics beyond high school level and is accessible to anyone with an introductory background in statistics.

Críticas:

'This is a welcome second edition of Dupont's book. It incorporates the changes in the STATA 10 command language that are designed to have a more uniform format across models. It also teaches how to look at the data with graphs, a very important part of teaching statistical data analysis to non-statisticians (and biostatistics graduate students!). This is one of the strengths of STATA and it is good to make use of it in a text. The topics are comprehensive and well developed. Moreover, this book will never get hidden on your desk or bookshelf. The shocking pink cover makes it stand out from almost any other book I have.' Teaching of Statistics in the Health Sciences

'With Stata, the author meets the demands of researchers who want to understand the methods without dipping into sophisticated mathematics. ... Although readers without prior training in biostatistics may benefit from the book, those with knowledge of introductory statistics would definitely benefit more. ... this is an ideal textbook for non-biostatistics graduate students for learning advanced biostatistics. It also serves as a good reference for biostatisticians in collaborative work.' Doody's Book Review

'...the second edition of this book is an excellent training and reference tool for young (as well as experienced) epidemiologic and biomedical researchers. It provides a comprehensive overview of traditional and novel approaches to model and interpret complex clinical, epidemiologic, and biomedical databases.' Stanley P. Azen, University of Southern California