European University Institute Library

Best practices in logistic regression, Jason W. Osborne, University of Louisville

eng

Includes bibliographical references and indexes

illustrations

index present

non fiction

Best practices in logistic regression

electronic resource

bibliographydictionaries

980877310

Jason W. Osborne, University of Louisville

SAGE research methods

Jason W. Osborne's Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers' basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne's applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.--, Provided by publisher

chapter 1. A conceptual introduction to bivariate logistic regression -- chapter 2. How does logistic regression handle a binary dependent variable? -- chapter 3. Performing simple logistic regression -- chapter 4. A practical guide to testing assumptions and cleaning data for logistic regression -- chapter 5. Continuous predictors : why splitting continuous variables into categories is undesirable -- chapter 6. Using unordered categorical independent variables in logistic regression -- chapter 7. Curvilinear effects in logistic regression -- chapter 8. Logistic regression with multiple independent variables : opportunities and pitfalls -- chapter 9. A brief overview of probit regression -- chapter 10. Replication and generalizability in logistc regression -- chapter 11. Modern and effective methods of dealing with missing data -- chapter 12. Multinomial and ordinal logistic regression -- chapter 13. Multilevel modeling with logistic regression

specialized