Multivariable analysis is a challenging subject for clinicians, whether they are novice researchers or trained practitioners. Most biostatistics books do not cover multivariable analysis, while existing multivariable analysis books are dense with mathematical formulas. Multivariable Analysis: A Practical Guide for Clinicians steps aside from mathematics to offer conceptual explanations. Dr Mitchell Katz follows a non-threatening, question-and-answer approach to explain how to perform and interpret multivariable analyses. He begins by explaining why clinicians should do multivariable analysis and then guides them through topics such as how to choose multivariable methods, analyse independent variables, and validate multivariable models. The book is loaded with useful tips, tables, figures, and references and examples from medical literature demonstrate real-world applications and uses of multivariable analysis. Multivariable Analysis: A Practical Guide for Clinicians is an indispensable guide for medical students, residents, and practising physicians.
Table of contents:
1. Introduction; 2. Common uses of multivariable models; 3. Outcome variables in multivariable analysis; 4. Independent variables in multivariable analysis; 5. Assumptions of multiple linear regression, logistic regression, and proportional hazard analysis; 6. Relationship of independent variables to one another; 7. Setting up a multivariable analysis: subjects; 8. Performing the analysis; 9. Interpreting the analysis; 10. Checking the assumptions of the analysis; 11. Validation of models; 12. Special topics; 13. Publishing your study; 14. Summary: steps for constructing a multivariable model.
Multivariable analysis is a challenging subject for clinicians, both novice researchers and trained practitioners alike. Multivariable Analysis: A Practical Guide for Clinicians presents conceptional explanations on how to perform and interpret multivariable analyses. It follows a non-threatening, question-and-answer approach and is loaded with useful tips, tables, figures, and references.
Multivariable Analysis: A Practical Guide for Clinicians explains, with little mathematics, how to perform and interpret multivariable analyses.
Table of contents:
1. Introduction; 2. Common uses of multivariable models; 3. Outcome variables in multivariable analysis; 4. Independent variables in multivariable analysis; 5. Assumptions of multiple linear regression, logistic regression, and proportional hazard analysis; 6. Relationship of independent variables to one another; 7. Setting up a multivariable analysis: subjects; 8. Performing the analysis; 9. Interpreting the analysis; 10. Checking the assumptions of the analysis; 11. Validation of models; 12. Special topics; 13. Publishing your study; 14. Summary: steps for constructing a multivariable model.
Multivariable analysis is a challenging subject for clinicians, both novice researchers and trained practitioners alike. Multivariable Analysis: A Practical Guide for Clinicians presents conceptional explanations on how to perform and interpret multivariable analyses. It follows a non-threatening, question-and-answer approach and is loaded with useful tips, tables, figures, and references.
Multivariable Analysis: A Practical Guide for Clinicians explains, with little mathematics, how to perform and interpret multivariable analyses.