TY - JOUR
T1 - Opportunities and Issues in Modeling Intensive Longitudinal Data
T2 - Learning from the COGITO Project
AU - West, Stephen G.
N1 - Funding Information:
Funding: This work was not supported by a grant.
Publisher Copyright:
© 2019, © 2019 Taylor & Francis Group, LLC.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2018/11/2
Y1 - 2018/11/2
N2 - Technological developments increasingly permit the collection of longitudinal data sets in which the data structure contains a large number of participants N and a large number of measurement occasions T. Promising new dynamical systems approaches to the analysis of large N, large T data sets have been proposed that utilize both between-subjects and within-subjects information. The COGITO project, begun over a decade ago, is an early large N = 204, large T = 100 study that collected high quality cognitive and psychosocial data. In this introduction, I describe the COGITO project and conceptual and statistical issues that arise in the analysis of large N, large T data sets. I provide a brief overview of the five papers in the special section which include conceptual pieces, a didactic presentation of a dynamic structural equation approach, and papers reporting new statistical analyses of the COGITO data set to answer substantive questions. Although many challenges remain, these new approaches offer the promise of improving scientific inquiry in the behavioral sciences.
AB - Technological developments increasingly permit the collection of longitudinal data sets in which the data structure contains a large number of participants N and a large number of measurement occasions T. Promising new dynamical systems approaches to the analysis of large N, large T data sets have been proposed that utilize both between-subjects and within-subjects information. The COGITO project, begun over a decade ago, is an early large N = 204, large T = 100 study that collected high quality cognitive and psychosocial data. In this introduction, I describe the COGITO project and conceptual and statistical issues that arise in the analysis of large N, large T data sets. I provide a brief overview of the five papers in the special section which include conceptual pieces, a didactic presentation of a dynamic structural equation approach, and papers reporting new statistical analyses of the COGITO data set to answer substantive questions. Although many challenges remain, these new approaches offer the promise of improving scientific inquiry in the behavioral sciences.
KW - between-subjects
KW - dynamic systems
KW - intensive longitudinal data
KW - within-subjects; time series
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U2 - 10.1080/00273171.2018.1545631
DO - 10.1080/00273171.2018.1545631
M3 - Article
C2 - 30744425
AN - SCOPUS:85061454375
SN - 0027-3171
VL - 53
SP - 777
EP - 781
JO - Multivariate Behavioral Research
JF - Multivariate Behavioral Research
IS - 6
ER -