Abstract
The aim of this study is to provide an empirical evaluation of the influence of different aspects of design in the context of factor analysis in terms of model stability. The overall model stability of factor solutions was evaluated by the examination of the order for testing three levels of Measurement Invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (Δx2) between two groups, and Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker-Lewis Index (TLI). Factorial invariance results revealed that the stability of the models was varying over increasing levels of measurement as a function of Variable-To-Factor (VTF) ratio, Subject-To-Variable (STV) ratio, and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratios 4:1, 7:1, and 10:1, the models started to show stability over the levels of measurement when the STV ratio was 4:1. Yet, the frequency of stability models over 1000 replications increased (from 77% to 91%) as the STV ratio increased. The models showed more stability at or above 32:1 STV.
Publisher
Engineering, Technology & Applied Science Research
Reference36 articles.
1. J. S. Tanaka, "'How Big Is Big Enough?': Sample Size and Goodness of Fit in Structural Equation Models with Latent Variables," Child Development, vol. 58, no. 1, pp. 134-146, 1987. https://doi.org/10.2307/1130296
2. J. J. Hox, C. J. Maas, and M. J. Brinkhuis, "The effect of estimation method and sample size in multilevel structural equation modeling," Statistica Neerlandica, vol. 64, no. 2, pp. 157-170, 2010. https://doi.org/10.1111/j.1467-9574.2009.00445.x
3. T. A. Holster, J. W. Lake, and W. R. Pellowe, "Measuring and predicting graded reader difficulty," Reading in a Foreign Language, vol. 29, no. 2, pp. 218-244, Oct. 2017.
4. S. Doi, M. Ito, Y. Takebayashi, K. Muramatsu, and M. Horikoshi, "Factorial validity and invariance of the Patient Health Questionnaire (PHQ)-9 among clinical and non-clinical populations," PLOS ONE, vol. 13, no. 7, 2018, Art. no. e0199235. https://doi.org/10.1371/journal.pone.0199235
5. T. A. Brown, Confirmatory Factor Analysis for Applied Research, Second Edition. New York ; London: Guilford Publications, 2015.
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献