Statistical Methods for the Analysis of Biomedical Data: Woolson/Statistical

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.Content: Chapter 1 Introduction (pages 1–8): Chapter 2 Descriptive Statistics (pages 9–48): Chapter 3 Basic Probability Concepts (pages 49–77): Chapter 4 Further Aspects of Probability (pages 79–118): Chapter 5 Confidence Intervals and Hypothesis Testing: General Considerations and Applications (pages 119–149): Chapter 6 Comparison of Two Groups: t?Tests and Rank Tests (pages 151–216): Chapter 7 Comparison of Two Groups: Chi?Square and Related Procedures (pages 217–262): Chapter 8 Tests of Independence and Measures of Association for Two Random Variables (pages 263–306): Chapter 9 Least?Squares Regression Methods: Predicting One Variable from Another (pages 307–357): Chapter 10 Comparing More than Two Groups of Observations: Analysis of Variance for Comparing Groups (pages 359–415): Chapter 11 Comparing More than Two Groups of Observations: Rank Analysis of Variance for Group Comparisons (pages 417–439): Chapter 12 Comparing More than Two Groups of Observations: Chi?Square and Related Procedures (pages 441–460): Chapter 13 Special Topics in Analysis of Epidemiologic and Clinical Data: Studying Association between a Disease and a Characteristic (pages 461–507): Chapter 14 Estimation and Comparison of Survival Curves (pages 509–540): Chapter 15 Multiple Linear Regression Methods: Predicting One Variable from Two or More Other Variables (pages 541–622):

Praise for the First Edition

This text is a very welcome addition to the field, both as a reference and classroom text.

-Publication of the International Statistical Institute

This book is a perfectly organized source of reference for elementary statistical procedures used in clinical trials.

-Biomedical Journal

I would recommend this book as an introductory biostatistics text for its clear presentation and worked examples, particularly in the chapters on the comparison of groups.

-Statistics in Medicine

Statistical Methods for the Analysis of Biomedical Data surveys a number of statistical topics commonly used in the analysis of biological and medical data, as well as several other topics such as observer agreement, standardization of rates, and methods for analysis of odds ratio. Applied in its approach, the book describes statistical procedures through the introduction of worked examples for each procedure.

The Second Edition includes a new chapter on multiple linear regression methods, new sections in each chapter on using SAS for computations, and revised and expanded problems. This authoritative volume also:

* Is organized by problem rather than method, guiding readers to the correct technique for solving the problem at hand

* Compares, in cases where more than one technique is applicable, the advantages and disadvantages of each option

* Develops, in detail, solutions to practical problems of design and analysis through worked examples

* Demonstrates how SAS output illustrates the results of analyses of true-to-life applications, such as predicting systolic blood pressure as a function of age, height, weight, and gender from data taken on Muscatine teenagers

* Includes methods for comparing two or more groups and evaluating the association between two variables, techniques for epidemiological analysis of 2x2 tables, and procedures for estimation and comparing survival curves

Statistical Methods for the Analysis of Biomedical Data makes an ideal reference for analysts and researchers in biostatistics, medicine, and other health-related fields, as well as a textbook for graduate courses in biostatistics.

Booknews

A number of statistical topics commonly used in the analysis of biological and medical data are surveyed, as well as other topics such as observer agreement, standardization of rates, and methods for analysis of odds ratio. Material is organized by problem rather than method, guiding readers to the correct technique for solving a specific problem. This second edition contains a new chapter on multiple linear regression methods, new sections on using SAS for computations, and expanded problems. The book can be used as a text for graduate courses in biostatistics, and as a reference for researchers and analysts in health-related fields. The authors teach biostatistics at the University of Iowa College of Public health. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Includes a chapter on multiple linear regression in biomedical research, with sections containing 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. "Statistical Methods for the Analysis of Biomedical Data makes an ideal reference for analysts and researchers in biostatistics, medicine, and other health-related fields, as well as a textbook for graduate courses in biostatistics."--Jacket