Model specification search using a genetic algorithm with factor reordering for a simple structure factor analysis model

Hiroto Murohashi, Hideki Toyoda

Research output: Contribution to journalArticle

2 Citations (Scopus)


Many techniques for automated model specification search based on numerical indices have been proposed, but no single decisive method has yet been determined. In the present article, the performance and features of the model specification search method using a genetic algorithm (GA) were verified. A GA is a robust and simple metaheuristic algorithm with great searching power. While there has already been some research applying metaheuristics to the model fitting task, we focus here on the search for a simple structure factor analysis model and propose a customized algorithm for dealing with certain problems specific to that situation. First, implementation of model specification search using a GA with factor reordering for a simple structure factor analysis is proposed. Then, through a simulation study using generated data with a known true structure and through example analysis using real data, the effectiveness and applicability of the proposed method were demonstrated.

Original languageEnglish
Pages (from-to)179-191
Number of pages13
JournalJapanese Psychological Research
Issue number3
Publication statusPublished - 2007 Sep



  • Combinational optimization problem
  • Factor analysis
  • Genetic algorithm
  • Model specification search
  • Structural equation modeling

ASJC Scopus subject areas

  • Psychology(all)

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