Biostatistics: A Methodology for the Health Sciences, 2nd Edition
| Authors: |
Gerald van Belle, Lloyd D. Fisher, Patrick J. Heagerty, and Thomas Lumley |
| Publisher: |
Wiley |
| Copyright: |
2004 |
| ISBN-10: |
0-471-03185-2 |
| ISBN-13: |
978-0-471-03185-7 |
| Pages: |
871; hardcover |
| Price: |
$112.00 |
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Comment from the Stata technical group
This text is useful as an introductory statistics text, as an advanced
biostatistics text for a graduate course or for professional self-study, and
as an encyclopedia of biostatistics and a valuable desk reference. At
almost 900 pages, it can easily serve in these three roles.
For the novice, some chapters of the text are similar to what you would find
in an introductory statistics textbook, including an overview of the role
that statistics plays in biomedical science, descriptive statistics, the
normal distribution, one- and two-sample inference of means and proportions,
issues associated with random sampling, contingency tables, linear models,
and ANOVA, among others.
For those needing an advanced statistics text or an introductory course in
biostatistics, there are chapters devoted to discrimination and
classification, principal component and factor analysis, epidemiological
tables, analysis of panel data, survival analysis, and randomized clinical
trials, to name a few. Each chapter also contains many exercises, making it
ideal for use in the classroom, as well as for self-study.
Finally, the authors have invested considerable effort in forming a
bibliography so complete that it may be used by advanced researchers wishing
to track down current literature. Since the bibliography is organized by
chapter, the reader has instant access to a reference list for any subfield
of biostatistics currently under study.
Table of contents
Preface to the First Edition
Preface to the Second Edition
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 and
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. Personal Postscript
Appendix
Author Index
Subject Index
Symbol Index
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