Influence of Sample Size, Estimation Method and Normality on Fit Indices in Confirmatory Factor Analysis
Journal: JOURNAL OF SOCIAL SCIENCES RESEARCH (Vol.9, No. 2)Publication Date: 2015-12-15
Authors : Murat Doğan;
Page : 1822-1833
Keywords : Confirmatory Factor Analysis; Monte Carlo Simulation; EQS; Structural Equation Modelling; Fit Indices;
Abstract
In this study, Monte Carlo simulation is used to evaluate the characteristics of CFA fit indices under different conditions (such as sample size, estimation method and distributional conditions). The simulation study was performed using seven different samples where sample has a different sample size such as 50, 100, 200, 400, 800, 1600, 4000, four different estimation methods (Maximum Likelihood, Generalized Least Square, Least Square and Weighted Least Square) and three distribution conditions (normal, slightly non-normal and moderately non-normal). A simulation study was conducted with EQS software to examine the effect of these conditions on the most common eleven fit indices that are studied in CFA and SEM. As a result of this study, all of the factors studied are shown to have an influence on the fit indices.
Other Latest Articles
- From digital pricing to digital marketing and digital distribution
- JUSTICE AND EMPOWERMENT IN THE CLASSROOM:THE SOCIAL EXCHANGE PERSPECTIVE
- Expansion Strategy Implementation for SMEs
- Strategy formulation for SMEs in Greece’s uncertain environment
- SPORTS AS A DYNAMIC FORCE IN DEVELOPING RELATIONS IN GLOBAL POLITICS
Last modified: 2016-07-05 19:32:45