Best Practices in Logistic Regression

Jason W. Osborne - Clemson University, USA

February 2014 | 488 pages | SAGE Publications, Inc

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.

Best Practices in Logistic Regression explains logistic regression in a concise and simple manner that gives students the clarity they need without the extra weight of longer, high-level texts.

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ISBN: 9781452244792 Paperback Suggested Retail Price: $126.00 Bookstore Price: $100.80

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1. A Conceptual Introduction to Bivariate Logistic Regression

2. Under the Hood with Logistic Regression

3. Performing Simple Logistic Regression

4. Conceptual and Practical Introduction to Testing Assumptions and Cleaning Data for Logistic Regression

5. Continuous Variables In Logistic Regression (And Why You Should Not Convert Them To Categorical Variables!)

6. Dealing with Unordered Categorical Predictors in Logistic Regression

7. Curvilinear Effects in Logistic Regression

8. Multiple Predictors in Logistic Regression (Including Interaction Effects)

9. A Brief Overview of Probit Regression

10. Logistic Regression and Replication: A Story Of Sample Size, Volatility, and Why Resampling Cannot Save Biased Samples but Data Cleaning And Independent Replication Can

11. Missing Data, Sample Size, Power, and Generalizability of Logistic Regression Analyses

12. Multinomial and Ordinal Logistic Regression: Modeling Dependent Variables with More Than Two Categories

13. Hierarchical Linear Models with Binary Outcomes: Multilevel Logistic Regression