Main description:

A new class of longitudinal data has emerged with the use of technological devices for scientific data collection. This class of data is called intensive longitudinal data (ILD). This volume features state-of-the-art applied statistical modelling strategies developed by leading statisticians and methodologists working in conjunction with behavioural scientists.

Contents:

Introduction: Intensive Longitudinal DataTheodore A. Walls and Joseph L. Schafer:
1: Theodore A. Walls, Hyekyung Jung, and Joseph E. Schwartz: Multilevel Models for Intensive Longitudinal Data
2: Joseph L. Schafer: Marginal Modeling of Intensive Longitudinal Data by Generalized Estimating Equations
3: Runze Li, Tammy L. Root, and Saul Shiffman: A Local Linear Estimation Procedure for Functional Multilevel Modeling
4: Donald Hedeker, Robin J. Mermelstein, and Brian R. Flay: Application of Item Response Theory Models for Intensive Longitudinal Data
5: Carlotta Ching Ting Fok and James O. Ramsay: Periodic Trends, Non-periodic Trends, and their Interactions in Longitudinal or Functional Data
6: Michael J. Rovine and Theodore A. Walls: Multilevel Autoregressive Modeling of Interindividual Differences in the Regularity of a Process
7: Moon-Ho Ringo Ho, Robert Shumway, and Hernando Ombao: The State-Space Approach to Modeling Dynamic Processes
8: James O. Ramsay: The Control of Behavioral Input/Output Systems
9: Steven M. Boker and Jean-Phillippe Laurenceau: Dynamical Systems Modeling: An Application to the Regulation of Intimacy and Disclosure in Marriage
10: Stephen L. Rathbun, Saul Shiffman, and Chad J. Gwaltney: Point Process Models for Event History Data: Applications ion the Behavioral Science
11: Sarah M. Nusser, Stephen S. Intille, and Ranjan Maitra: Emerging Technologies and Next Generation Intensive Longitudinal Data Collection