Comparative Performance of Estimation Maximization Among Residual Estimators: A Structural Equation Modelling Perspective

Autor:	Albert Luguterah, A. R. Abdul-Aziz, Bashiru I. I. Saeed
Rok vydání:	2021
Předmět:	Estimation Perspective (graphical) Applied mathematics Estimator Maximization Residual Structural equation modeling Regression Mathematics
Zdroj:	International Journal of Statistics and Probability. 10:138
ISSN:	1927-7040 1927-7032
DOI:	10.5539/ijsp.v10n2p138
Popis:	As the concept of methodology has advanced, varied methods of estimating residuals have been developed including regression method, Bartlett’s method and Anderson-Rubin’s method. The study utilized estimation maximization approach together with other methods of estimating residuals under the structural equation model. The results showed that the strength of the existing methods in structural equation modelling are the weaknesses of the estimation maximization method, and vice versa. It was, therefore, found that from the comparative model fit information that the Bartlett’s based method gave better residual parameter estimates compared to the Regression based and the Anderson Rubin based methods. However, the estimation maximization method gave better residual parameter estimates than the other three existing methods; the Regression, Bartlett’s and the Anderson Rubin based methods.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32aa915449c0a26fda228fe633af83da https://doi.org/10.5539/ijsp.v10n2p138 Zobrazit plný text záznamu