COMPARATIVE FIT INDEXES IN STRUCTURAL MODELS
COMPARATIVE FIT INDEXES IN STRUCTURAL MODELS
复制标题
DOI：
10.1037/0033-2909.107.2.238
复制
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
赋范拟合指数和非赋范拟合指数经常用作卡方统计量的检验，以评估结构模型的拟合。现有指数的一个缺点是，他们估计没有已知的人口参数。提出了一个新的系数来概括两个嵌套模型的非中心性参数的相对减少。系数的两个估计量产生新的赋范（CFI）和非赋范（FI）拟合指数。CFI避免了Bentler和Bonett（1980）的赋范拟合指数（NFI）在小样本中经常注意到的拟合低估。FI是Bentler和Bonett的非赋范拟合指数（NNFI）的线性函数，避免了NNFI中经常出现的极端低估和高估。渐近地，CFI，FI，NFI和Bollen开发的一个新指数是比较拟合的等价度量，而NNFI通过比较每个自由度的非中心性来度量相对拟合。所有的指数都被推广到允许使用Wald和拉格朗日乘数统计。一个例子说明了正确规范和错误规范的条件下，这些指标的行为。新的拟合指数在所有样本量下均表现良好。
Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model. A drawback of existing indexes is that they estimate no known population parameters. A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models. Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes. CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI). FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI. Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom. All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics. An example illustrates the behavior of these indexes under conditions of correct specification and misspecification. The new fit indexes perform very well at all sample sizes.