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Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data
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| List Price: | £40.00 |
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Product Description
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.
Product Details
- Amazon Sales Rank: #1023184 in Books
- Published on: 2002-11-28
- Released on: 2008-08-21
- Original language: English
- Number of items: 1
- Binding: Paperback
- 408 pages
Editorial Reviews
Review
‘I highly recommend Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data. I believe that it will be much appreciated by biomedical researchers who are eager to learn more about statistical modeling. I also believe that biostatisticians will enjoy using this book for teaching and consulting purposes.’ Teaching of Statistics in the Health Services
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.
