A Comparison of Accuracy Based on Data Imputation between Unconstrained Structural Equation Modeling and Weighted Least Squares Regression

Abstract:

This research proposed a comparison of accuracy based on data imputation between unconstrained structural equation modeling (Uncon-SEM) and weighted least squares (WLS) regression. This model is developed by University of California, Irvine (UCI) and measured using the mean magnitude of relative error (MMRE). Experimental data set is created using the waveform generator that contained 21 indicators (1,200 samples) and divided into two groups (1,000 for training and 200 for testing groups). In fact, training group was analyzed by three main factors (F1, F2, and F3) for creating the models. The result of the experiment show MMRE of Uncon-SEM method based on the testing group is 34.29% (accuracy is 65.71%). In contrast, WLS method produces MMRE for testing group is 55.54% (accuracy is 44.46%). So, Uncon-SEM is high accuracy and MMRE than WLS method that is 21.25%.

• Periodical: Applied Mechanics and Materials (Volumes 130-134)
• Pages: 730-733
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.130-134.730
• Online since: October 2011
• Authors: Narong Phothi, Somchai Prakancharoen
• Keywords: Data Imputation, Structural Equation Modeling (SEM), Unconstrained Structural Equation Modeling, Weighted Least Squares Regression

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