The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories Article

Usami, Satoshi, Jacobucci, Ross, Hayes, Timothy. (2019). The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories . COMPUTATIONAL STATISTICS, 34(1), 1-22. 10.1007/s00180-018-0815-x

Open Access International Collaboration

cited authors

  • Usami, Satoshi; Jacobucci, Ross; Hayes, Timothy

authors

publication date

  • March 1, 2019

published in

keywords

  • CART
  • Classification
  • Decision trees
  • Latent change score model
  • Longitudinal data
  • MIXTURE-MODELS
  • Mathematics
  • Model misspecification
  • Physical Sciences
  • SELECTION
  • Science & Technology
  • Statistics & Probability

Digital Object Identifier (DOI)

publisher

  • SPRINGER HEIDELBERG

start page

  • 1

end page

  • 22

volume

  • 34

issue

  • 1