Statistical modeling biomedical researcher second edition

1722

收藏 2011-09-29

Editorial ReviewsReview"This is a welcome edition of Dupont's book. The topics are comprehensive and well developed."
Ray Hoffmann, The Medical College of Wisconsin for the Teaching Statistics in Health Sciences Newsletter

"Although readers without prior training in biostatistics may benefit from the book, those with knowledge of introductory statistics would definitely benefit more. Traditional biomedical researchers may have a bit of difficulty in understanding some complex concepts without further communication with biostatisticians. Thus, 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 Review Service

"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. In addition, an excellent and popular statistical package (Stata), widely used in the epidemiologic research population, is presented and demonstrated by using real data sets."
Stanley P. Azen, American Journal of Epidemiology

Product DescriptionFor biomedical researchers, the new edition of this standard text guides readers 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. The Stata statistical software package is used to perform the analyses, in this edition employing the intuitive version 10.
Topics covered include linear, logistic and Poisson regression, survival analysis, fixed-effects analysis of variance, and repeated-measure analysis of variance. Restricted cubic splines are used to model non-linear relationships. Each method is introduced in its simplest form and then extended to cover more complex situations. An appendix will help the reader select the most appropriate statistical methods for their data. The text makes extensive use of real data sets available online through Vanderbilt University.