The effect of different data structures, sample sizes on model fit measures

被引：28

作者：

Dogan, Ilkay ^{[1
]}

Ozdamar, Kazim ^{[2
]}

机构：

[1] Afyon Kocatepe Univ, Dept Biostat, Fac Vet Med, TR-03200 Afyon, Turkey

[2] Eskisehir Osmangazi Univ, Fac Med, Dept Biostat, Eskisehir, Turkey

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2017年 / 46卷 / 09期

关键词：

Model fit measures; Optimization; Parameter estimation methods; Simulation study; Structural equation modeling; CONFIRMATORY FACTOR-ANALYSIS; GOODNESS-OF-FIT; IMPROPER SOLUTIONS; INDEXES; PARAMETER; NUMBER; SPECIFICATION; NONNORMALITY; SENSITIVITY; ERROR;

D O I：

10.1080/03610918.2016.1241409

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this study, our aim was to investigate the changes of different data structures and different sample sizes on the structural equation modeling and the influence of these factors on the model fit measures. Examining the created structural equation modeling under different data structures and sample sizes, the evaluation of model fit measures were performed with a simulation study. As a result of the simulation study, optimization and negative variance estimation problems have been encountered depending on the sample size and changing correlations. It was observed that these problems disappeared either by increasing the sample size or the correlations between the variables in factor. For upcoming studies, the choice of RMSEA and IFI model fit measures can be suggested in all sample sizes and the correlation values for data sets are ensured the multivariate normal distribution assumption.

引用

页码：7525 / 7533

页数：9

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