### 抜粋

Model selection is one of the most important steps in the application of structural equation modeling (SEM). In this process, the likelihood ratio test statistic, T, is a commonly employed index. Hypothesis testing can be performed on the basis that T asymptotically follows the χ^{2} distribution. Various fit indices have been proposed, most of which are based on the assumption that T asymptotically follows the χ^{2} distribution. When the size of the sample is small, however, the distribution of T deviates considerably from the χ^{2} distribution. This problem, especially pronounced when there is a large number of indicators per factor, is serious because it violates the theoretical justification of utilizing for model selection not only T, but also many other fit indices. In the present article, we propose a Bartlett correction of T to improve its approximation to the χ^{2} distribution. When the efficacy of our method was evaluated by Monte Carlo simulation, the results showed that this method was superior to the current standard.

元の言語 | English |
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ページ（範囲） | 382-392 |

ページ数 | 11 |

ジャーナル | Japanese Journal of Educational Psychology |

巻 | 55 |

発行部数 | 3 |

DOI | |

出版物ステータス | Published - 2007 9 |

外部発表 | Yes |

### ASJC Scopus subject areas

- Education
- Developmental and Educational Psychology

## フィンガープリント Bartlett correction of test statistics in structural equation modeling' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

## これを引用

*Japanese Journal of Educational Psychology*,

*55*(3), 382-392. https://doi.org/10.5926/jjep1953.55.3_382