Data Analytic Techniques for Dynamical Systems

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Synopsis

Each volume in the Notre Dame Series on Quantitative Methodology features leading methodologists and substantive experts who provide instruction on innovative techniques designed to enhance quantitative skills in a substantive area. This latest volume focuses on the methodological issues and analyses pertinent to understanding psychological data from a dynamical system perspective. Dynamical systems analysis (DSA) is increasingly used to demonstrate time-dependent variable change. It is used more and more to analyze a variety of psychological phenomena such as relationships, development and aging, emotional regulation, and perceptual processes. The book opens with the best occasions for using DSA methods. The final two chapters focus on the application of dynamical systems methods to problems in psychology such as substance use and gestural dynamics. In addition, it reviews how and when to use:

time series models from a discrete time perspective

stochastic differential equations in continuous time


estimating continuous time differential equation models


multilevel models of differential equations to estimate within-person dynamics and the corresponding population means


new SEM models for dynamical systems data

Data Analytic Techniques for Dynamical Systems is beneficial to advanced students and researchers in the areas of developmental psychology, family studies, language processes, cognitive neuroscience, social and personality psychology, medicine, and emotion. Due to the book’s instructive nature, it serves as an excellent text for advanced courses on this particular technique.

Book details

Series:
Notre Dame Series On Quantitative Methodology Ser.
Author:
Steven M. Boker, Michael J. Wenger
ISBN:
9781135611538
Related ISBNs:
9780203936757, 9780805850130, 9780805850130, 9780805850123, 9780805850123
Publisher:
Taylor and Francis
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2020-04-25
Usage restrictions:
Copyright
Copyright date:
2007
Copyright by:
Lawrence Erlbaum Associates, Publishers 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Medicine, Nonfiction, Psychology