Statistical Methods for the Analysis of Biomedical Data

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John Wiley & Sons, Jan 25, 2011 - Medical - 712 pages
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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.
 

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Contents

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 tTests and Rank Tests
151
7 Comparison of Two Groups ChiSquare and Related Procedures
217
8 Tests of Independence and Measures of Association for Two Random Variables
263
10 Comparing More than Two Groups of 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 ChiSquare 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

9 LeastSquares Regression Methods Predicting One Variable from Another
307

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About the author (2011)

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.

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