Latent growth curve model selection with Tabu search

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is illustrated using empirical data along with an easy to use computerized implementation.

Original languageEnglish (US)
Pages (from-to)153-159
Number of pages7
JournalInternational Journal of Behavioral Development
Volume45
Issue number2
DOIs
StatePublished - Mar 2021

Bibliographical note

Publisher Copyright:
© The Author(s) 2020.

Keywords

  • Latent growth curve model
  • Tabu search
  • model selection

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