Full Description
Now in its fourth edition, this best-selling, highly praised text has been fully revised and updated with expanded sections on propensity analysis, sensitivity analysis, and emulation trials. As before, it focuses on easy-to follow explanations of complicated multivariable techniques including logistic regression, proportional hazards analysis, and Poisson regression. The perfect introduction for medical researchers, epidemiologists, public health practitioners, and health service researchers, this book describes how to preform and interpret multivariable analysis, using plain language rather than mathematical formulae. It takes advantage of the availability of user-friendly software that allow novices to conduct complex analysis without programming experience; ensuring that these analyses are set up and interpreted correctly. Numerous tables, graphs, and tips help to demystify the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the published literature that enable readers to model their analyses after well conducted research, increasing chances of top-tier publication.
Contents
1. Introduction; 2. Common uses of multivariable models; 3. Outcome variables in multivariable analysis; 4. Independent variables in multivariable analysis; 5. Relationship of independent variables to one another; 6. Setting up a multivariable analysis; 7. Performing the analysis; 8. Interpreting the results; 9. Delving deeper: checking the underlying assumptions of the analysis; 10. Propensity scores; 11. Correlated observations; 12. Sensitivity Analysis; 13. Validation of models; 14. Special topics; 15. Publishing your study; 16. Summary: Steps for constructing a multivariable model; Index.
