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Multivariable Analysis
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Table of Contents

Preface; 1. Introduction; 2. Common uses of multivariable models; 3. Outcome variables in multivariable analysis; 4. Type of independent variables in multivariable analysis; 5. Assumptions of multiple linear regression, multiple 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; Index.

Promotional Information

The third edition of this highly successful text enables clinical researchers to set up, perform and interpret multivariable models.

About the Author

Mitchell H. Katz is Clinical Professor of Medicine, Epidemiology and Biostatistics at the University of California, San Francisco, Attending Physician at the San Francisco General Hospital, and Director of the San Francisco Department of Public Health, San Francisco, USA.

Reviews

Reviews of the second edition: 'Katz provides a comprehensive review of multivariable analysis to illuminate an often confusing topic for clinicians, particularly clinician scientists. The chapter on the assumptions of multivariable analysis provides excellent examples and tips throughout.' Myra A. Kleinpeter, Journal of the National Medical Association
'This book had an enthusiastic first outing, and certainly this second edition is worth the price for a good reference.' Kentucky Medical Journal

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