WSEAS Transactions on Mathematics
Print ISSN: 1109-2769, E-ISSN: 2224-2880
Volume 20, 2021
Research on Structural Flexibility and Acceptance Model (SFAM) Reconstruction Based on Disruption Innovation in the Social Humanities and Education Sector
Authors: , , , , ,
Abstract: The research objectives are as follows: (1) Developing a flexible structural model of the relationship between variables. (2) Develop a structural model that is robust with the assumptions of normality and homoscedasticity. (3) Obtain estimator properties from the flexible and robust SFAM structural model. (4) Obtaining hypothesis testing of each relationship constructed from a flexible and robust SFAM structural model. This research is integrated with a flexible and robust model approach based on nonparametric smoothing spline (RNSS) regression analysis which can capture the form of relationships that depend on empirical data, and the robustness of the model based on the distribution assumption and the assumption of homoscedasticity error variance. There are at least three transformation methods, namely SRS, MSI, and RASCH, which will be used in the development of the Structural Flexibility and Acceptance Model (SFAM). The results obtained from the research progress report are obtaining the development of a flexible structural model of the form of the relationship between variables, obtaining the development of a robust structural model of the assumptions of normality and homoscedasticity, obtaining the estimator properties of the flexible and robust SFAM structural model, and obtaining hypothesis testing. of each relationship constructed from a flexible and robust SFAM structural model. The originality of the theory in this study is very visible in the discovery of a new model, namely SFAM which can accommodate several things, which are the weaknesses of several existing analysis tools such as reciprocal and recursive models, more than one endogenous variable, flexible and robust models, overcoming inadmissible solutions, reflective indicators, formative , and reflective/formative (on the second-order), metric and non-metric data, and simultaneous processing of the input score data (through transformation to scale).
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Pages: 657-675
DOI: 10.37394/23206.2021.20.70