Generalized Ordinal Logistic Regression Model On Data Modeling Student Pesantren Value FMIPA Islamic University of Bandung Year 2017

Nia Astuti, Anneke Iswani Achmad, Nusar Hajarisman

Abstract


Logistic regression is one method that can be used to get functional relationship between categorical response variable with predictor variable. There are several kinds of logistic regression one of them is Generalized Ordinal Logistic Regression Model. This regression describes the functional relationship between the response variable that is ordinal and the predictor variable. This paper will discuss the use of Generalized Ordinal Logistic Regression Model on new students' pesantren exam data at Faculty of Mathematics and Natural Sciences (F-MIPA) of Islamic University of Bandung in 2017. Parameter estimation is done using likelihood maximum method, then solving nonlinear equations from Log-likelihood functions are estimated by numerical methods using the Newton-Raphson iteration process. Test of model significance using likelihood ratio test.

Keywords


Logistic Regression, Generalized Ordinal Logistic Regression Model, Maximum Likelihood, Newton-Raphson, Likelihood Ratio

References


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DOI: http://dx.doi.org/10.29313/.v0i0.8149

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