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

Rating: (9 reviews) Author: William D. Dupont ISBN : 9780521614801 New from $60.14 Format: PDF

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For 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.

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• Product Details
• Table of Contents
• Reviews

• Series: Cambridge Medicine
• Paperback: 542 pages
• Publisher: Cambridge University Press; 2 edition (February 23, 2009)
• Language: English
• ISBN-10: 0521614805
• ISBN-13: 978-0521614801
• Product Dimensions: 1 x 6.8 x 9.6 inches
• Shipping Weight: 2.3 pounds (View shipping rates and policies)

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

I used this book as the text for a biostatistics class that used STATA as the statistitical package. I found the organization, problems, and the STATA output the book provides, all very helpful. In addition, as I moved systematically through the book, the tips regarding using the STATA features were key to my learning many of the practical aspects of the STATA program.

By KC

Dupont's "Statistical Modeling for Biomedical Researchers" is an accessible, straightforward, easy-to-read text for students and/or researchers w/ some elementary background in biostatistics. As previous reviewers have indicated, this is largely a problem-based text, so for those of you who seek a detailed theoretical explanation of the tools presented therein, you may want to look elsewhere. A major advantage, however, is Dupont's presentation of how to run the respective analyses using the statistical software package, Stata, although it should be noted that the syntax presented is for version 7 of Stata -- not version 8. Parenthetically, all of the code -- w/ the exception of the graphing commands -- are essentially the same between versions. In short, this text is a good introduction to some of the techniques typically not discussed in an elementary biostatistics course, although the book is best characterized as an invaluable adjunct to more theoretical, comprehensive biostatistics textbooks.

By kthdimension