構造方程式モデリングは, 因子分析, 分散分析, バス解析のすべてにとって代わるのか?  [in Japanese] Does Structural Equation Modeling Outperform Traditional Factor Analysis. Analysis of Variance and Path Analysis?  [in Japanese]

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Author(s)

Abstract

It is well-known that structural equation modeling (SEM) can represent a variety of traditional multivariate statistical models. This fact does not necessarily mean that SEM should be used for the traditional models. It is often said that a general model is more difficult to handle than a specific model developed for a given situation. In this paper, we shall clarify relative advantages between SEM and several traditional statistical models. Rather than comparison in mathematical properties, we shall discuss how and when SEM outperforms corresponding traditional models in practical situations. Special attention is paid to statistical analysis of a scale score, the sum of indicator variables determined by factor analysis. In particular, we shall study relative advantages between (i) confirmatory factor analysis and exploratory factor analysis, (ii) multiple indicator analysis and correlational and regression analysis of scale scores, (iii) analysis of factor means and analysis of variance of scale scores, and (iv) path analysis and multiple regression analysis.

Journal

  • The Japanese journal of behaviormetrics

    The Japanese journal of behaviormetrics 29(2), 138-159, 2002-12-25

    The Behaviormetric Society of Japan

References:  32

Cited by:  20

Codes

  • NII Article ID (NAID)
    110003812515
  • NII NACSIS-CAT ID (NCID)
    AN0008437X
  • Text Lang
    JPN
  • Article Type
    Journal Article
  • ISSN
    03855481
  • NDL Article ID
    6613024
  • NDL Source Classification
    ZE1(社会・労働--社会科学・社会思想・社会学) // ZD43(経済--統計)
  • NDL Call No.
    Z6-1106
  • Data Source
    CJP  CJPref  NDL  NII-ELS 
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