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Biostatistics (Hardback)
Biostatistics (Hardback)
Author: van Belle, Gerald
Edition/Copyright: 2ND 04
ISBN: 0-471-03185-2
Publisher: John Wiley & Sons, Inc.
Type: Print On Demand
Used Print:  $165.00
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Author Bio
Summary
Table of Contents
 
  Author Bio
GERALD VAN BELLE is a professor in the Departments of Biostatistics and Environmental and Occupational Health Sciences at the University of Washington in Seattle, Washington. He is the author of four books as well as more than 100 articles and numerous book chapters.
LLOYD D. FISHER is Professor Emeritus in the Department of Biostatistics at the University of Washington, Seattle, and a consultant to the drug and device industries. He has held positions with the Center for AIDS Research, the Mayo Clinic, and the Fred Hutchinson Cancer Center, among others.
PATRICK J. HEAGERTY is an associate professor in the Department of Biostatistics at the University of Washington in Seattle and an associate member at the Fred Hutchinson Cancer Research Center.
THOMAS LUMLEY is an associate professor in the Department of Biostatistics at the University of Washington in Seattle.
 
  Summary
THOMAS S. LUMLEY and GERALD VAN BELLE
* Data sets, tables, additional examples, and solutions to selected problems will be housed on the web
* Instructors will have the opportunity to submit their own problems and solutions to be added to the website (with proper citations)
* Authors will comprehensively update all the material in the book, focusing on current techniques and applications
* An additional appendix will mention current software packages, web sites, and important data sets that are available to students and practitioners
 
  Table of Contents
1. Introduction to Biostatistics.

2. Biostatistical Design of Medical Studies.

3. Descriptive Statistics.

4. Statistical Inference: Populations and Samples.

5. One- and Two-Sample Inference.

6. Counting Data.

7. Categorical Data: Contingency Tables.

8. Nonparametric, Distribution-Free and Permutation Models: Robust Procedures.

9. Association and Prediction: Linear Models with One Predictor Variable.

10. Analysis of Variance.

11. Association and Prediction: Multiple Regression Analysis, Linear Models with Multiple Predictor Variables.

12. Multiple Comparisons.

13. Discrimination and Classification.

14. Principal Component Analysis and Factor Analysis.

15. Rates and Proportions.

16. Analysis of the Time to an Event: Survival Analysis.

17. Sample Sizes for Observational Studies.

18. Longitudinal Data Analysis.

19. Randomized Clinical Trials.

20. A Personal Postscript.

 

 

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