Applied Longitudinal Data Analysis

PART I; 1. A framework for investigating change over time; 2. Exploring Longitudinal Data on Change; 3. Introducing the multilevel model for change; 4. Doing data analysis with the multilevel mode for change; 5. Treating TIME more flexibly; 6. Modelling discontinuous and nonlinear change; 7. Examining the multilevel model's error covariance structure; 8. Modelling change using covariance structure analysis; PART II; 9. A Framework for Investigating Event Occurrence; 10. Describing discrete-time event occurrence data; 11. Fitting basic Discrete-Time Hazard Models; 12. Extending the Discrete-Time Hazard Model; 13. Describing Continuous-Time Event Occurrence Data; 14. Fitting Cox Regression Models; 15. Extending the Cox Regression Model