Modeling Self-Regulation as a Process Usinga Multiple Time-Scale Multiphase Latent Basis Growth Model

Jonathan Lee Helm, Nilam Ram, Pamela M. Cole, Sy Miin Chow

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)635-648
Number of pages14
JournalStructural Equation Modeling
Volume23
Issue number5
DOIs
StatePublished - Sep 2 2016

All Science Journal Classification (ASJC) codes

  • General Decision Sciences
  • General Economics, Econometrics and Finance
  • Sociology and Political Science
  • Modeling and Simulation

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