Statistical Methods for Modeling Human Dynamics: An Interdisciplinary Dialogue

Author:   Sy-Miin Chow (University of North Carolina - Chapel Hill, USA) ,  Emilio Ferrer (University of California, USA) ,  Fushing Hsieh (University of California, Davis, USA)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781848728257


Pages:   444
Publication Date:   09 December 2009
Format:   Hardback
Availability:   In Print   Availability explained
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Statistical Methods for Modeling Human Dynamics: An Interdisciplinary Dialogue


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Author:   Sy-Miin Chow (University of North Carolina - Chapel Hill, USA) ,  Emilio Ferrer (University of California, USA) ,  Fushing Hsieh (University of California, Davis, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   Routledge
Dimensions:   Width: 15.20cm , Height: 2.80cm , Length: 22.90cm
Weight:   0.980kg
ISBN:  

9781848728257


ISBN 10:   1848728255
Pages:   444
Publication Date:   09 December 2009
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

This is a timely and important book that addresses an integrated set of topics that will be of great interest to a broad audience of researchers studying human dynamics. The contributors are among the leaders in their respective fields and jointly represent a truly interdisciplinary perspective on these issues. The material is presented in both an accessible and technically rigorous manner, and real data examples help clarify key points throughout. Importantly, this text offers a collection of papers that challenge many traditional beliefs held about the typical analysis of repeated measures data. I recommend this book highly. - Patrick J. Curran, University of North Carolina, Chapel Hill Dynamical modeling of intraindividual change and variability obtained from many sources and in a wide range of time scales is the promising future of behavioral science research and the availability of this outstanding volume will accelerate our progress in that direction. Take it home, take it to the office, take it to class and, whatever you do, take it seriously! - John R. Nesselroade, University of Virginia Intensive longitudinal designs will be providing cutting edge insights into psychological, neuroscience and biomedical processes during the next decades, and researchers using these designs will want to study the useful approaches described in this volume. I consider this book to be required reading! - Patrick E. Shrout, New York University I am delighted to see this outstanding volume containing contributions connecting mathematics, classical and Bayesian statistics, signal processing and psychology. .. Other subject matter areas could well take this volume as a model for presenting the results of collaborative research in their own fields. -Robert H. Shumway, University of California, Davis


Author Information

Sy-Miin Chow is Assistant Professor of Psychology at the University of North Carolina at Chapel Hill. She received her Ph.D. in Quantitative Psychology from the University of Virginia. Her research focuses on the development and adaptation of modeling and analysis tools for evaluating linear and nonlinear dynamical systems models. Dr. Chow received the prestigious Dissertation Award from the Society of Multivariate Experimental Psychology in 2004. Emilio Ferrer is Associate Professor of Psychology at the University of California, Davis. He received his Ph.D. in Quantitative Psychology from the University of Virginia. His research focuses on methods techniques for studying change and intra-individual variability in developmental processes. Dr. Ferrer received the prestigious Dissertation Award from the Society of Multivariate Experimental Psychology in 2002. Fushing Hsieh is Professor of Statistics at the University of California, Davis. He received his Ph.D. in Statistics from Cornell University. Dr. Hsieh's research focuses on survival analysis, modeling in biomedical dynamic systems and in animal behavior, evolutionary ecology and aging, and the analysis of cognitive processing. A frequent contributor to Biometrika and the Journal of the Royal Statistical Society Series B, Dr. Hsieh served as an Associate Editor of Statistica Sinica from 1998 until 2005.

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