Multivariable Analysis
Multivariable Analysis
$62.00
USDThis new edition has been fully revised to build on the enormous success of its popular predecessor. It now includes new features introduced by readers' requests including a new chapter on propensity score, more detail on clustered data and Poisson regression and a new section on analysis of variance. As before it describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It is the perfect introduction for all clinical researchers. It focuses on the nuts and bolts of performing research and prepares the reader to perform and interpret multivariable models. Numerous tables, graphs and tips help to simplify and explain the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research.
- Provides a nonmathematical introduction
- Nuts and bolts practical approach for clinical relevance
- Provides answers to basic questions
Reviews & endorsements
"Our background in basic statistics is typically primitive and certainly could use some help in understanding what we read. This very readable and even interesting 200 plus page book really fills that need...The index is complete and very pointed, making the reader able to use the book not only to learn the subject but to refer back to previous reading."
Kentucky Medical Journal
"It lays out some of the most common forms of regression... in prose that is easily digested by anyone with an appreciation for the subject of Statistics. The descriptions are highlighted by dozens of examples, including tables and graphs from published medical studies.... I would have no qualms about recommending these books to colleagues wanting a better understanding of the goals and limitations of analysis..."
Biometrics, March, 2007
"The exposition... is greatly enhanced by the author's choice of excellent examples demonstrating many of the methodologies, including relevant tables and figures, culled and referenced from the clinical literature... a useful introduction to a novice investigator, especially for those with little access to a biostatistician."
Charles L. Liss, Merck Research Labs for The American Statistician
"I would recommend this book to anyone who wants to learn (or teach) statistics in the health sciences. This is a must-read, practical statistics book for clinical researchers."
Ayumi Shintani, Vanderbuilt University for Teaching Statistics in Health Sciences Newsletter
Product details
May 2012Adobe eBook Reader
9781139239264
0 pages
0kg
26 b/w illus. 15 tables
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- Preface
- 1. Introduction
- 2. Common uses of multivariable models
- 3. Outcome variables in multivariable analysis
- 4.Types of independent variables in multivariable analysis
- 5. Assumptions of multiple linear regression, logistic regression, and proportional hazards analysis
- 6. Relationship of independent variables to one another
- 7. Setting up a multivariable analysis
- 8. Performing the analysis
- 9. Interpreting the analysis
- 10. Checking the assumptions of the analysis
- 11. Propensity scores
- 12. Correlated observations
- 13. Validation of models
- 14. Special topics
- 15. Publishing your study
- 16. Summary: steps for constructing a multivariable model.
