Aplikasi Model Persamaan Struktural pada Program R (Studi Kasus Data Pengukuran Kecerdasan)

https://doi.org/10.24042/ajpm.v6i1.56

Achi Rinaldi

Abstract


Structural Equation Model (SEM) was known as powerfull and popular multivariate analysis technique. It provides a comprehensive method for the quantification and testing of theories. The ability of this model is to test model with multiple dependent that more powerfull than multiple regression, it’s also can make some simultaneously model in one form. Data was used from Holzinger and Swineford that measured intellegence in several indicator. This model was lack of form and performance that can be showed in value of Chi-square. Akaike Information Criterion (AIC) and Chi-square value for specificly in  block “male” was less than “female”,  so the result gave structural model for block male was better than female.


Keywords


Structural Equation Model

References


Allison, P. (1999). Multiple Regression: A Primer. London Pine Forge Press.

Becker, R. A., Chambers, J. M., &Wilks, A. R. (1988). The new S language: A programming environment for data analysis and graphics. Pacific Grove, CA: Wadsworth.

Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

Chambers, J. M. (1998). Programming with data: A guide to the S language. New York: Springer.

Fox, J. (2006). Structural equation modeling with the sem package in r. Structural Equation Modeling, 13(3), 465-486.

Holzinger, K. J. and Swineford, F. A. (1939). A study in factor analysis: The stability of a bi-factor solution. Supplementary Education Monographs, 48. University of Chicago.

Huang, B., Thornhill, N., Shah, S. and Shook, D (2002). Path analysis for process trobleshooting. Proceedings of Advanced Control of Industrial Process, Kumamoto, Japan, 10-12 Juni, 149-154.




DOI: https://doi.org/10.24042/ajpm.v6i1.56

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