Statistical Methods for the Analysis of Biomedical Data

The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.

• Organized by problem rather than method, so it guides readers to the correct technique for solving the problem at hand.

Auteur

ROBERT F. WOOLSON, PhD, is a Professor of Biostatistics and Associate Dean for Research at the University of Iowa College of Public Health.

WILLIAM R. CLARKE, PhD, is a Professor of Biostatistics at the University of Iowa College of Public Health.

Contenu

Dedication v

Preface to the 1987 Edition xvii

Preface to the 2002 Edition xxi

Acknowledgment xxiii

1 Introduction 1

2 Descriptive Statistics 9

3 Basic Probability Concepts 49

4 Further Aspects of Probability 79

5 Confidence Intervals and Hypothesis Testing: General Considerations and Applications 119

6 Comparison of Two Groups: t-Tests and Rank Tests Introduction 151

7 Comparison of Two Groups: Chi-Square and Related Procedures 217

8 Tests of Independence and Measures of Association for Two Random Variables 263

9 Least-Squares Regression Methods: Predicting One Variable from Another 307

10 Comparing More than Two Groups Observations: Analysis of Variance for Comparing Groups 359

11 Comparing More than Two Groups of Observations: Rank Analysis of Variance for Group Comparisons 417

12 Comparing More than Two Groups of Observations: Chi-Square and Related Procedures 441

13 Special Topics in Analysis of Epidemiologic and Clinical Data: Studying Association between a Disease and a Characteristic 461

14 Estimation and Comparison of Survival Curves 509

15 Multiple Linear Regression Methods: Predicting One Variable from Two or More Other Variables 541

Appendix 623

Topic Index 673