skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Models for Intensive Longitudinal Data

ISBN: 9780198038665 ;ISBN: 0198038666 ;ISBN: 9780195173444 ;ISBN: 0195173449 ;EISBN: 9780199847051 ;EISBN: 0199847053 ;EISBN: 9780198038665 ;EISBN: 0198038666 ;EISBN: 019029163X ;EISBN: 9780190291631 ;DOI: 10.1093/acprof:oso/9780195173444.001.0001 ;OCLC: 71810603

Full text available

Citations Cited by
  • Title:
    Models for Intensive Longitudinal Data
  • Author: Walls, Theodore A ; Schafer, Joseph L
  • Schafer, Joseph L ; Walls, Theodore A ; Walls, Theodore A
  • Subjects: Datenanalyse ; Datenerfassung ; Gesundheitswissenschaften ; Item-Response-Theorie ; Lehrbuch ; Longitudinal method ; Longitudinal studies ; Längsschnittuntersuchung ; Mehrebenenanalyse ; Messverfahren ; Methodologie ; Modell ; Probabilities & applied mathematics ; Social Psychology ; Social sciences ; Sozialforschung ; Sozialwissenschaften ; Statistical methods ; Statistische Methode ; Verhaltensforschung
  • Description: 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 the statistical 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 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 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. (DIPF/Orig.).
  • Publisher: New York: Oxford University Press
  • Creation Date: 2006
  • Format: XXII, 288
  • Language: English
  • Identifier: ISBN: 9780198038665
    ISBN: 0198038666
    ISBN: 9780195173444
    ISBN: 0195173449
    EISBN: 9780199847051
    EISBN: 0199847053
    EISBN: 9780198038665
    EISBN: 0198038666
    EISBN: 019029163X
    EISBN: 9780190291631
    DOI: 10.1093/acprof:oso/9780195173444.001.0001
    OCLC: 71810603
  • Source: Ebook Central Academic Complete
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait