Throughout the book the author uses simple, intuitive examples from a range of disciplines to demonstrate important aspects of logistic regression and its many uses. The author explains these concepts clearly and seeks to further developed students' understanding with the use of cases, vignettes and a multitude of figures and tables. INDICE: 1. A Conceptual Introduction to Bivariate Logistic Regression2. Under the Hood with Logistic Regression3. Performing Simple Logistic Regression4. Conceptual and Practical Introduction to Testing Assumptions and Cleaning Data for Logistic Regression5. Continuous Variables In Logistic Regression (And Why You Should Not Convert Them To Categorical Variables!)6. Dealing with Unordered Categorical Predictors in Logistic Regression7. Curvilinear Effects in Logistic Regression8. Multiple Predictors in Logistic Regression (Including Interaction Effects)9. A Brief Overview of Probit Regression10. Logistic Regression and Replication: A Story Of Sample Size, Volatility, and Why Resampling Cannot Save Biased Samples but Data Cleaning And Independent Replication Can11. Missing Data, Sample Size, Power, and Generalizability of Logistic Regression Analyses12. Multinomial and Ordinal Logistic Regression: Modeling Dependent Variables with More Than Two Categories13. Hierarchical Linear Models with Binary Outcomes: Multilevel Logistic Regression
- ISBN: 978-1-4522-4479-2
- Editorial: SAGE Publications, Inc
- Encuadernacion: Rústica
- Páginas: 512
- Fecha Publicación: 31/05/2014
- Nº Volúmenes: 1
- Idioma: