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

10 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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