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

Dupont, William D.

ISBN 10: 0521655781 / ISBN 13: 9780521655781

Published by Cambridge University Press, 2002

About this Item

Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.

Seller Inventory # 18644085-20

Bibliographic Details

• Title: Statistical Modeling for Biomedical Researchers : A Simple Introduction to the Analysis of Complex Data
• Publisher: Cambridge University Press
• Publication Date: 2002
• Language: English
• ISBN 10: 0521655781
• ISBN 13: 9780521655781
• Binding: Soft cover
• Edition: 1st Edition.
• Condition: Good
• Weight: 2.284 pounds

About this title

Synopsis

This text will enable biomedical researchers to use a number of advanced statistical methods that have proven valuable in medical research. It is intended for people who have had an introductory course in biostatistics. A statistical software package (Stata) is used to avoid mathematics beyond the high school level. The emphasis is on understanding the assumptions underlying each method, using exploratory techniques to determine the most appropriate method, and presenting results in a way that will be readily understood by clinical colleagues. Numerous real examples from the medical literature are used to illustrate these techniques. Graphical methods are used extensively. Topics covered include linear regression, logistic regression, Poisson regression, survival analysis, fixed-effects analysis of variance, and repeated-measures analysis of variance. Each method is introduced in its simplest form and is then extended to cover situations in which multiple explanatory variables are collected on each study subject.

About the Author

Educated at McGill University, and the Johns Hopkins University, Bill Dupont is presently Professor and Director of the Division of Biostatistics at Vanderbilt University School of Medicine. He is best known for his work on the epidemiology of breast cancer, but has also published papers on power calculations, the estimation of animal abundance, the foundations of statistical inference, and other topics.