Models for Intensive Longitudinal Data (Hardcover)
Language: English
Published by Oxford University Press Inc, New York, 2006
- Hardcover
- New

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Hardcover. 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 for collecting 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 thestatistical models in this volume are applicable to a range of data. The volume features state-of-the-art statistical modeling strategies developed by leading statisticians and methodologists workingon 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 andapplying a given model. The chapters highlight issues of general concern in modeling these kinds of data, such as a focus on regulatory systems, issues of curve registration, variable frequency and spacing ofmeasurements, complex multivariate patterns of change, and multiple independent series. The extraordinary breadth of coverage makes this an indispensable reference for principal investigators 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 contains program examples and documentation. A new class of longitudinal data has emerged with the use of technological devices for scientific data collection. This class of data is called intensive longitudinal data(ILD). This volume features state-of-the-art applied statistical modeling strategies developed by leading statisticians and methodologists working in conjunction with behavioral scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9780195173444
- Title
- Models for Intensive Longitudinal Data (Hardcover)
- Author
- Theodore A. Walls
- Publisher
- Oxford University Press Inc, New York
- Publication year
- 2006
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0195173449
- ISBN 13
- 9780195173444
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 kinds of 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 principal investigators 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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About the Author
Joseph L. Schafer, Ph.D., is Associate Professor of Statistics and an Investigator at The Methodology Center at The Pennsylvania State University. Dr. Schafer has developed techniques for analyzing incomplete data and incorporating missing-data uncertainty into statistical inference. His areas of research also include latent-class and latent transition analysis, nonsampling errors in surveys and censuses, strategies for statistical computing and software development, and statistical methods for casual inference.
"About the title" may belong to another edition of this title.
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