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.
How to perform and interpret multivariable analysis, using plain language rather than complex derivations.
'This book had an enthusiastic first outing, and certainly this second edition is worth the price for a good reference.' Kentucky Medical Journal
Ask a Question About this Product More... |