TY - JOUR
T1 - Modeling Self-Regulation as a Process Usinga Multiple Time-Scale Multiphase Latent Basis Growth Model
AU - Helm, Jonathan Lee
AU - Ram, Nilam
AU - Cole, Pamela M.
AU - Chow, Sy Miin
N1 - Funding Information:
This work was supported by the National Institute on Health (R01 HD076994, R24 HD041025, UL TR000127, R01 GM105004, MH 61388, and HD 076994), the National Science Foundation (SES-1357666), and the Penn State Social Science Research Institute.
Publisher Copyright:
Copyright © Taylor & Francis Group, LLC.
PY - 2016/9/2
Y1 - 2016/9/2
N2 - Measurement burst designs, wherein individuals are measured intensively during multiple periods (i.e., bursts), have created new opportunities for studying change at multiple time scales. This article develops a model that might be useful in situations where the functional form of short-term change is unknown, might consist of multiple phases, and might change over the long term. Specifically, we combine measurement of intraindividual entropy, a latent basis growth model, a multiphase growth model, and a growth model with covariates into a unified framework that could help accommodate the complexity of patterns that emerge in multiple time-scale categorical data streams. Empirical data from a longitudinal study of young children’s behavior during laboratory tasks designed to induce frustration are used to illustrate the utility of the proposed model for simultaneously describing intratask (short-term) change in self-regulation and developmental (long-term) shifts in intratask change.
AB - Measurement burst designs, wherein individuals are measured intensively during multiple periods (i.e., bursts), have created new opportunities for studying change at multiple time scales. This article develops a model that might be useful in situations where the functional form of short-term change is unknown, might consist of multiple phases, and might change over the long term. Specifically, we combine measurement of intraindividual entropy, a latent basis growth model, a multiphase growth model, and a growth model with covariates into a unified framework that could help accommodate the complexity of patterns that emerge in multiple time-scale categorical data streams. Empirical data from a longitudinal study of young children’s behavior during laboratory tasks designed to induce frustration are used to illustrate the utility of the proposed model for simultaneously describing intratask (short-term) change in self-regulation and developmental (long-term) shifts in intratask change.
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U2 - 10.1080/10705511.2016.1178580
DO - 10.1080/10705511.2016.1178580
M3 - Article
AN - SCOPUS:84969731067
SN - 1070-5511
VL - 23
SP - 635
EP - 648
JO - Structural Equation Modeling
JF - Structural Equation Modeling
IS - 5
ER -