Regime-Switching Bivariate Dual Change Score Model

Sy Miin Chow, Kevin J. Grimm, Guillaume Filteau, Conor V. Dolan, John J. McArdle

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Mixture structural equation model with regime switching (MSEM-RS) provides one possible way of representing over-time heterogeneities in dynamic processes by allowing a system to manifest qualitatively or quantitatively distinct change processes conditional on the latent "regime" the system is in at a particular time point. Unlike standard mixture structural equation models such as growth mixture models, MSEM-RS allows individuals to transition between latent classes over time. This class of models, often referred to as regime-switching models in the time series and econometric applications, can be specified as regime-switching mixture structural equation models when the number of repeated measures involved is not large. We illustrate the empirical utility of such models using one special case-a regime-switching bivariate dual change score model in which two growth processes are allowed to manifest regime-dependent coupling relations with one another. The proposed model is illustrated using a set of longitudinal reading and arithmetic performance data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 study (ECLS-K; U.S. Department of Education, National Center for Education Statistics, 2010).

Original languageEnglish (US)
Pages (from-to)463-502
Number of pages40
JournalMultivariate Behavioral Research
Volume48
Issue number4
DOIs
StatePublished - Jul 2013
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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