Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways; the elderly become frail and forgetful. In addition to these natural changes, targeted interventions may cause change: cholesterol levels may decline as a result of a new medication, exam grades may rise following completion of a coaching class. By measuring and charting changes like these - both naturalistic and experimentally induced - researchers uncover the temporal nature of development. The investigation of change has fascinated empirical researchers for generations, and to do it well, they must have longitudinal data. "Applied Longitudinal Data Analysis" is a much-needed professional book that will instruct readers in the many new methodologies, now at their disposal to make the best use of longitudinal data, including both individual growth modelling and survival analysis. Throughout the chapters, the authors employ many cases and examples from a variety of disciplines, covering multilevel models, curvilinear and discontinuous change, in addition to discrete-time hazard models, continuous-time event occurrence, and Cox regression models. "Applied Longitudinal Data Analysis" is a unique contribution to the literature on research methods and will be useful to a wide range of behavioural and social science researchers.
1 A Framework for Investigating Change over Time 3
2 Exploring Longitudinal Data on Change 16
3 Introducing the Multilevel Model for Change 45
4 Doing Data Analysis with the Multilevel Model for Change 75
5 Treating TIME More Flexibly 138
6 Modeling Discontinuous and Nonlinear Change 189
7 Examining the Multilevel Model's Error Covariance Structure 243
8 Modeling Change Using Covariance Structure Analysis 266
9 A Framework for Investigating Event Occurrence 305
10 Describing Discrete-Time Event Occurrence Data 325
11 Fitting Basic Discrete-Time Hazard Models 357
12 Extending the Discrete-Time Hazard Model 407
13 Describing Continuous-Time Event Occurrence Data 468
14 Fitting Cox Regression Models 503
15 Extending the Cox Regression Model 543
Notes 607
References 613
