Table of Contents
Contents: Preface. Part I: Analyzing Change in Multiple Subjects.D. Rogosa, Myths and Methods: "Myths About Longitudinal Research" plus Supplemental Questions. G.P. Sackett, J.W. Shortt, Hierarchical Regression Analysis with Repeated Data Measures. G.R. Patterson, Orderly Change in a Stable World: The Antisocial Trait as a Chimera. M. Stoolmiller, Using Latent Growth Curve Models to Study Developmental Processes. E.R. Anderson, Accelerating and Maximizing Information from Short-Term Longitudinal Research. S.W. Raudenbush, Hierarchical Linear Models to Study the Effects of Social Context on Development. J.B. Willett, J.D. Singer, Investigating Onset, Cessation, Relapse, and Recovery: Using Discrete-Time Survival Analysis to Examine the Occurrence and Timing of Critical Events. M. Stoolmiller, L. Bank, Autoregressive Effects in Structural Equation Models: We See Some Problems. Part II: Analyzing Change in a Single Subject or an Interacting System.R. Bakeman, L.B. Adamson, P. Strisik, Lags and Logs: Statistical Approaches to Interaction (SPSS Version). W.A. Griffin, Assessing State Changes in Micro-Social Interaction: An Introduction to Event-History Analysis. W. Gardner, On the Reliability of Sequential Data: Measurement, Meaning, and Correction. J. Crosbie, Interrupted Time-Series Analysis with Short Series: Why It Is Problematic; How It Can Be Improved. M.B. Priestly, Current Developments in Time-Series Modeling. J. Murray, Nonlinear Dynamics and Chaos. G.L. Baker, The Chaotic Pendulum: Model and Metaphor.
