Are the Signs of Factor Loadings Arbitrary in Confirmatory Factor Analysis? Problems and Solutions
Dandan Tang1, Steven M Boker1, Xin Tong1
1University of Virginia.
Structural Equation Modeling : a Multidisciplinary Journal
|March 5, 2025
Summary
The replication crisis in social sciences is partly due to issues with analytical tools like confirmatory factor analysis (CFA). This study addresses inaccurate factor-loading sign estimation in CFA, proposing effective solutions.
Area of Science:
- Social and Behavioral Sciences
- Psychometrics
- Statistical Modeling
Background:
- The replication crisis in social and behavioral sciences highlights concerns about study reliability and validity.
- Existing research often overlooks analytical tool issues contributing to this crisis.
- Confirmatory Factor Analysis (CFA) is a widely used tool where factor-loading sign estimation is a critical, yet often neglected, aspect.
Purpose of the Study:
- To investigate the problem of accurately estimating factor-loading signs in Confirmatory Factor Analysis (CFA) models.
- To identify the drawbacks of current methods in estimating these crucial signs.
- To propose and validate effective solutions for accurate factor-loading sign estimation.
Main Methods:
- Empirical demonstration of the factor-loading sign estimation problem.
- Monte Carlo simulation studies to rigorously assess estimation accuracy.
- Development and testing of novel solutions to improve sign estimation.
Main Results:
- Current methods for estimating factor-loading signs in CFA exhibit significant drawbacks.
- Incorrect factor-loading signs can substantially distort the relationship between observed variables and latent factors.
- The three proposed solutions were empirically demonstrated to be effective in addressing the estimation problem.
Conclusions:
- Accurate estimation of factor-loading signs is essential for reliable and valid results in CFA.
- The proposed solutions offer practical and effective means to improve the accuracy of factor-loading sign estimation.
- Addressing this analytical issue can contribute to enhancing the overall rigor and replicability of social and behavioral research.
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