The Effects of Different Correlation Types on Goodness-of-Fit Indices in First Order and Second Order Factor Analysis for Multiple Choice Test Data
Halil Yurdugül.
Abstract
This study explores the effects of different correlation types (covariance and correlation matrix, obtained from Pearson, Goodman, and Tetrachoric) on goodness-of-fit indices in first order and second order factor analysis. The data included Math and Science subsets in Student Selection and Placement Examination for Secondary Education test administered in 2001 with the participation of 553108 students. A first-order and second-order confirmatory factor analyses were performed on the matrix from item scores obtained from several correlation coefficients. The findings indicate that when second order factor loadings (first order correlations) were equal, solutions with Pearson correlation coefficients yielded the most satisfactory goodness-of-fit. When second order factor loadings (first order correlations) were not equal, solutions with tetrachoric correlations yielded the most satisfactory goodness-of-fit.
The articles in Bibliomed are open access articles licensed under Creative Commons Attribution 4.0 International License (CC BY), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
We use cookies and other tracking technologies to work properly, to analyze our website traffic, and to understand where our visitors are coming from. More InfoGot It!
