Models For Intensive Longitudinal Data

Hardcover | June 29, 2006

EditorTheodore A. Walls, Joseph L. Schafer

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Rapid technological advances in devices used for data collection have led to the emergence of a new class of longitudinal data: intensive longitudinal data (ILD). Behavioral scientific studies now frequently utilize handheld computers, beepers, web interfaces, and other technological tools forcollecting many more data points over time than previously possible. Other protocols, such as those used in fMRI and monitoring of public safety, also produce ILD, hence the statistical models in this volume are applicable to a range of data. The volume features state-of-the-art statisticalmodeling strategies developed by leading statisticians and methodologists working on ILD in conjunction with behavioral scientists. Chapters present applications from across the behavioral and health sciences, including coverage of substantive topics such as stress, smoking cessation, alcohol use,traffic patterns, educational performance and intimacy. Models for Intensive Longitudinal Data (MILD) is designed for those who want to learn about advanced statistical models for intensive longitudinal data and for those with an interest in selecting and applying a given model. The chapters highlight issues of general concern in modeling these kindsof data, such as a focus on regulatory systems, issues of curve registration, variable frequency and spacing of measurements, complex multivariate patterns of change, and multiple independent series. The extraordinary breadth of coverage makes this an indispensable reference for principalinvestigators designing new studies that will introduce ILD, applied statisticians working on related models, and methodologists, graduate students, and applied analysts working in a range of fields. A companion Web site at www.oup.com/us/MILD contains program examples and documentation.

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Rapid technological advances in devices used for data collection have led to the emergence of a new class of longitudinal data: intensive longitudinal data (ILD). Behavioral scientific studies now frequently utilize handheld computers, beepers, web interfaces, and other technological tools forcollecting many more data points over time ...

Theodore A. Walls, Ph.D., is Professor of Psychology at the University of Rhode Island. As a research scientist at The Methodology Center at The Pennsylvania State University, Dr. Walls developed methods for the analysis of intensive longitudinal data and convened the international study group whose work led to the publication of thi...

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Models for Intensive Longitudinal Data
Models for Intensive Longitudinal Data

Kobo ebook|Jan 19 2006

$77.99

Format:HardcoverDimensions:320 pages, 6.42 × 9.29 × 0.91 inPublished:June 29, 2006Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195173449

ISBN - 13:9780195173444

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Table of Contents

Introduction: Intensive Longitudinal DataTheodore A. Walls and Joseph L. Schafer: 1. Theodore A. Walls, Hyekyung Jung, and Joseph E. Schwartz: Multilevel Models for Intensive Longitudinal Data2. Joseph L. Schafer: Marginal Modeling of Intensive Longitudinal Data by Generalized Estimating Equations3. Runze Li, Tammy L. Root, and Saul Shiffman: A Local Linear Estimation Procedure for Functional Multilevel Modeling4. Donald Hedeker, Robin J. Mermelstein, and Brian R. Flay: Application of Item Response Theory Models for Intensive Longitudinal Data5. Carlotta Ching Ting Fok and James O. Ramsay: Periodic Trends, Non-periodic Trends, and their Interactions in Longitudinal or Functional Data6. Michael J. Rovine and Theodore A. Walls: Multilevel Autoregressive Modeling of Interindividual Differences in the Regularity of a Process7. Moon-Ho Ringo Ho, Robert Shumway, and Hernando Ombao: The State-Space Approach to Modeling Dynamic Processes8. James O. Ramsay: The Control of Behavioral Input/Output Systems9. Steven M. Boker and Jean-Phillippe Laurenceau: Dynamical Systems Modeling: An Application to the Regulation of Intimacy and Disclosure in Marriage10. Stephen L. Rathbun, Saul Shiffman, and Chad J. Gwaltney: Point Process Models for Event History Data: Applications ion the Behavioral Science11. Sarah M. Nusser, Stephen S. Intille, and Ranjan Maitra: Emerging Technologies and Next Generation Intensive Longitudinal Data Collection

Editorial Reviews

"[Models for Intensive Longitudinal Data] addresses most of the researchers in the behavioral and related sciences, such as psychology, sociology, education, economics, management, and medical sciences. The book also addresses methodologists and statisticians, who are professionally dealingwith longitudinal analysis, to enhance their knowledge of the type of model covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of longitudinal analysis in solving their problems."--Psychometrika