COMPARATIVE FIT INDEXES IN STRUCTURAL MODELS
COMPARATIVE FIT INDEXES IN STRUCTURAL MODELS
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DOI：
10.1037/0033-2909.88.3.588
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发表时间：
1990-03-01
影响因子：
22.4
通讯作者：
BENTLER, PM
中科院分区：
文献类型：
--
作者：
BENTLER, PM
因子分析、路径分析、结构方程模型和相关的多元统计方法都是基于协方差结构模型（CSM）的最大似然或广义最小二乘估计。大样本理论提供了一种卡方拟合优度检验，用于将模型（M）与基于相关变量的一般替代方案M进行比较。建议这种比较不足以进行M评价。一个一般的空M的基础上修改变量之间的独立性，提出了一个额外的参考点的统计和科学评估的CSM。在顺序评估各组参数的统计必要性的过程中使用空M将协方差结构分析中的统计方法置于更完整的框架中。介绍了理想M_s检验和伪卡方检验的概念，阐述了它们在假设检验中的作用。还强调了补充统计评价与增量拟合指数与层次MS的比较的重要性。规范和nonnormed适合指数的开发和说明。(43参考）（PsycINFO数据库记录（c）2016阿帕，保留所有权利）
Factor analysis, path analysis, structural equation modeling, and related multivariate statistical methods are based on maximum likelihood or generalized least squares estimation developed for covariance structure models (CSMs). Large-sample theory provides a chi-square goodness-of-fit test for comparing a model (M) against a general alternative M based on correlated variables. It is suggested that this comparison is insufficient for M evaluation. A general null M based on modified independence among variables is proposed as an additional reference point for the statistical and scientific evaluation of CSMs. Use of the null M in the context of a procedure that sequentially evaluates the statistical necessity of various sets of parameters places statistical methods in covariance structure analysis into a more complete framework. The concepts of ideal Ms and pseudo chi-square tests are introduced, and their roles in hypothesis testing are developed. The importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical Ms is also emphasized. Normed and nonnormed fit indices are developed and illustrated.(43 ref)(PsycINFO Database Record (c) 2016 APA, all rights reserved)