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Multivariable Analysis Mitchell H. Katz (University of California, San Francisco)

Multivariable Analysis von Mitchell H. Katz (University of California, San Francisco)

Multivariable Analysis Mitchell H. Katz (University of California, San Francisco)


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Zusammenfassung

This 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.

Multivariable Analysis Zusammenfassung

Multivariable Analysis: A Practical Guide for Clinicians Mitchell H. Katz (University of California, San Francisco)

This 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.

Multivariable Analysis Bewertungen

'This book had an enthusiastic first outing, and certainly this second edition is worth the price for a good reference.' Kentucky Medical Journal

Inhaltsverzeichnis

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.

Zusätzliche Informationen

GOR005765131
9780521549851
052154985X
Multivariable Analysis: A Practical Guide for Clinicians Mitchell H. Katz (University of California, San Francisco)
Gebraucht - Sehr Gut
Broschiert
Cambridge University Press
20060209
220
N/A
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