Individual Pathways of Change
Statistical Models for Analyzing Learning and Development
Will be published approx. on 15. May 2010
Book
Hardback
227 pages
978-1-4338-0772-5 (ISBN)
Description
Individual Pathways of Change 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.
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.
More details
Series
Language
English
Place of publication
Washington DC
United States
Target group
Professional and scholarly
Dimensions
Height: 254 mm
Width: 178 mm
ISBN-13
978-1-4338-0772-5 (9781433807725)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.
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.
Content
Contributors
Series Foreword
Preface
Introduction
-Peter C. M. Molenaar and Karl M. Newell
I. Life Span Development
Person-Specific Analysis of the Dynamics of Weight Change
-Eric Loken
Neuromodulation of Fluctuations of Information Processing: Computational, Neural, and Genetic Perspectives
-Shu-Chen Li
Modeling Retest and Aging Effects in a Measurement Burst Design
-Martin Sliwinski, Lesa Hoffman, and Scott Hofer
Modeling Mother amp ndash Infant Interactions Using Hidden Markov Models
-Michael J. Rovine, Katerina O. Sinclair, and Cynthia A. Stifter
II. Dynamics of Learning
Decomposing the Performance Dynamics of Learning Through Time Scales
-Karl M. Newell, Gottfried Mayer-Kress, S. Lee Hong, and Yeou-Teh Liu
A State Space Approach to Representing Discontinuous Shifts in Change Processes
-Sy-Miin Chow and Guillaume Filteau
A Framework for Discrete Change
-Ingmar Visser, Brenda R. J. Jansen, and Maarten Speekenbrink
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
Regime-Switching Models to Study Psychological Process
-Ellen L. Hamaker, Raoul P. P. P. Grasman, and Jan Henk Kamphuis
Standard Error Estimation in Stationary Multivariate Time Series Models Using Residual-Based Bootstrap Procedures
-Guangjian Zhang and Sy-Miin Chow
Modeling Resilience With Differential Equations
-Steven M. Boker, Mignon A. Montpetit, Michael D. Hunter, and Cindy S. Bergeman
IV. Reflections and Prospects
On an Emerging Third Discipline of Scientific Psychology
-John R. Nesselroade
Index
About the Editors
Series Foreword
Preface
Introduction
-Peter C. M. Molenaar and Karl M. Newell
I. Life Span Development
Person-Specific Analysis of the Dynamics of Weight Change
-Eric Loken
Neuromodulation of Fluctuations of Information Processing: Computational, Neural, and Genetic Perspectives
-Shu-Chen Li
Modeling Retest and Aging Effects in a Measurement Burst Design
-Martin Sliwinski, Lesa Hoffman, and Scott Hofer
Modeling Mother amp ndash Infant Interactions Using Hidden Markov Models
-Michael J. Rovine, Katerina O. Sinclair, and Cynthia A. Stifter
II. Dynamics of Learning
Decomposing the Performance Dynamics of Learning Through Time Scales
-Karl M. Newell, Gottfried Mayer-Kress, S. Lee Hong, and Yeou-Teh Liu
A State Space Approach to Representing Discontinuous Shifts in Change Processes
-Sy-Miin Chow and Guillaume Filteau
A Framework for Discrete Change
-Ingmar Visser, Brenda R. J. Jansen, and Maarten Speekenbrink
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
Regime-Switching Models to Study Psychological Process
-Ellen L. Hamaker, Raoul P. P. P. Grasman, and Jan Henk Kamphuis
Standard Error Estimation in Stationary Multivariate Time Series Models Using Residual-Based Bootstrap Procedures
-Guangjian Zhang and Sy-Miin Chow
Modeling Resilience With Differential Equations
-Steven M. Boker, Mignon A. Montpetit, Michael D. Hunter, and Cindy S. Bergeman
IV. Reflections and Prospects
On an Emerging Third Discipline of Scientific Psychology
-John R. Nesselroade
Index
About the Editors