Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks: Examining Velocity and Acceleration of Growth Trajectories

Kevin Grimm, Zhiyong Zhang, Fumiaki Hamagami, Michèle Mazzocco

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of rates of change and acceleration in latent growth curves-information available indirectly through traditional growth curve models when change patterns are nonlinear with respect to time. To illustrate this approach, exponential growth models in the three frameworks are fit to longitudinal response time data from the Math Skills Development Project (Mazzocco & Meyers, 2002, 2003). We highlight the additional information gained from fitting growth curves in these frameworks as well as limitations and extensions of these approaches.

Original languageEnglish (US)
Pages (from-to)117-143
Number of pages27
JournalMultivariate Behavioral Research
Volume48
Issue number1
DOIs
StatePublished - Jan 2013
Externally publishedYes

Fingerprint

Nonlinear Modeling
Trajectory
Growth Curve
Growth
Growth Curve Model
Structural Equation Model
Exponential Model
Rate of change
Exponential Growth
Growth Model
Response Time
Structural Models
Reaction Time
Framework
Modeling

ASJC Scopus subject areas

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

Cite this

Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks : Examining Velocity and Acceleration of Growth Trajectories. / Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michèle.

In: Multivariate Behavioral Research, Vol. 48, No. 1, 01.2013, p. 117-143.

Research output: Contribution to journalArticle

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