How Do Orders Impact Structural Equation Model? Empirical Evidence from Patient Satisfaction
Zhihan Liu
Abstract
Open-access reader
Zhihan Liu
Abstract
Open-access reader
There haven’t been enough empirical evidences of orders’ impact on structural equation model and satisfaction index results. This study is conducted to figure out the problem by making a comparison between the first-order and high-order structural equation models building with the same sample from healthcare. As expected, results showed that the path coefficients and goodness-of-fit indices of high-order structural equation model were basically the same with its counterpart, suggesting the structural equation model’s orders would not affect the index and play the role of simplifying the model. Besides, compared with the conventional first-order structural equation model in patient satisfaction, the high-order model tended to be an improvement, for providing the probability of analyzing intermediate latent variables and forming the theoretical basis of multi-level structural equation modeling study.
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There haven’t been enough empirical evidences of orders’ impact on structural equation model and satisfaction index results. This study is conducted to figure out the problem by making a comparison between the first-order and high-order structural equation models building with the same sample from healthcare. As expected, results showed that the path coefficients and goodness-of-fit indices of high-order structural equation model were basically the same with its counterpart, suggesting the structural equation model’s orders would not affect the index and play the role of simplifying the model. Besides, compared with the conventional first-order structural equation model in patient satisfaction, the high-order model tended to be an improvement, for providing the probability of analyzing intermediate latent variables and forming the theoretical basis of multi-level structural equation modeling study.
Key concepts: Structural equation modeling, Goodness of fit, Psychology, Latent variable, Path coefficient, Order (exchange), Path analysis (statistics), Econometrics