Individual Pathways of Change: Statistical Models for Analyzing Learning and Development

Pages: 227
Item #: 4318077
ISBN: 978-1-4338-0772-5
List Price: $39.95
Member/Affiliate Price: $29.95
Copyright: 2010
Format: Hardcover
Availability: In Stock
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Overview

Individual Pathways of Change in Learning and Development presents and applies cutting-edge time series analysis techniques for analyzing intra-individual change. Editors Peter C. M. Molenaar and Karl M. Newell demonstrate the practical benefits of intra-individual analysis by not only applying the new techniques to various learning or developmental problems, but also discussing implications for future applications.

The techniques in this book cover each of Bartholomew's four classes of dynamic latent variable models, and they are presented and applied to a wide range of topics, such as measuring shifts between different psychological states, differences in responses and test scores, and time scales that are present in the growth or decay of learning processes. The editors emphasize innovative frameworks and reveal the limitations of using group between-subject analysis to derive inferences about psychological processes.

With more examples and contexts than any other book on the subject, this book is essential reading for students, professors, and researchers interested in the analysis of intra-individual change in learning and development.

Table of Contents

Contributors

Series Foreword

Preface

Introduction
—Peter C. M. Molenaar and Karl M. Newell

I. Life Span Development

  1. Person-Specific Analysis of the Dynamics of Weight Change
    —Eric Loken
  2. Neuromodulation of Fluctuations of Information Processing: Computational, Neural, and Genetic Perspectives
    —Shu-Chen Li
  3. Modeling Retest and Aging Effects in a Measurement Burst Design
    —Martin Sliwinski, Lesa Hoffman, and Scott Hofer
  4. Modeling Mother–Infant Interactions Using Hidden Markov Models
    —Michael J. Rovine, Katerina O. Sinclair, and Cynthia A. Stifter

II. Dynamics of Learning

  1. Decomposing the Performance Dynamics of Learning Through Time Scales
    —Karl M. Newell, Gottfried Mayer-Kress, S. Lee Hong, and Yeou-Teh Liu
  2. A State Space Approach to Representing Discontinuous Shifts in Change Processes
    —Sy-Miin Chow and Guillaume Filteau
  3. A Framework for Discrete Change
    —Ingmar Visser, Brenda R. J. Jansen, and Maarten Speekenbrink
  4. State Space Methods for Item Response Modeling of Multisubject Time Series
    —Peter van Rijn, Conor V. Dolan, and Peter C. M. Molenaar

III. Modeling Issues

  1. Regime-Switching Models to Study Psychological Process
    —Ellen L. Hamaker, Raoul P. P. P. Grasman, and Jan Henk Kamphuis
  2. Standard Error Estimation in Stationary Multivariate Time Series Models Using Residual-Based Bootstrap Procedures
    —Guangjian Zhang and Sy-Miin Chow
  3. Modeling Resilience With Differential Equations
    —Steven M. Boker, Mignon A. Montpetit, Michael D. Hunter, and Cindy S. Bergeman

IV. Reflections and Prospects

  1. On an Emerging Third Discipline of Scientific Psychology
    —John R. Nesselroade

Index

About the Editors

Editor Bios

Peter C. M. Molenaar, PhD, is a professor of human development in the Department of Human Development and Family Studies at The Pennsylvania State University, State College.

The general theme of his work involves the application of mathematical theories in the following fields of research:

  • singularity theory (in particular, catastrophe theory) to study developmental stage transitions,
  • nonlinear signal analysis techniques to map theoretical models of cognitive information processing onto dynamically interacting neural sources,
  • ergodic theory to study the relationships between intraindividual (idiographic) analyses and interindividual (nomothetic) analyses of psychological processes,
  • advanced multivariate analysis techniques in quantitative genetics and developmental psychology,
  • adaptive resonance theory neural networks to study the effects of nonlinear epigenetic processes, and
  • computational control techniques to optimally guide developmental psychological processes and disease processes of individual subjects in real time.

Karl M. Newell, PhD, is the Marie Underhill Noll Chair of Human Performance and head of the Department of Kinesiology at The Pennsylvania State University, State College.

Dr. Newell's research interests lie in the area of human movement in general and motor learning and control specifically. His research focuses on the coordination, control, and skill of normal and abnormal human movement across the life span; developmental disabilities and motor skills; and the influence of drug and exercise on movement control.

One of the specific themes of his research is the study of variability in human movement and posture, with specific reference to the onset of aging and Parkinson's disease. His other major research theme is processes of change in motor learning and development—the focus of this book.