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.
Inhaltsangabe
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.
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.
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