Abstract

Ordinal logistic regression is a statistical method used to analyze the ordinal response variable with three or more categories and predictor variables that are categorical or continuous. The use of ordinal response variables is common in scientific research. We develop an extension of the bivariate ordinal logistic regression model with two correlated response variables in which the relationship between the continuous predictor variable and its logit is modeled as a polynomial form, so it is called the Bivariate Polynomial Ordinal Logistic Regression (BPOLR) model. The aims of this study are determine parameter estimators of the BPOLR model using the Maximum Likelihood Estimation (MLE) method and obtain algorithms of estimating parameters of the BPOLR model. Based on the first partial derivatives, the results are not closed-form. Therefore, it is needed a numerical optimization to obtain the maximum likelihood estimator, namely the Berndt-Hall-Hall-Hausman (BHHH) method.

Original languageEnglish
Title of host publication8th International Conference and Workshop on Basic and Applied Science, ICOWOBAS 2021
EditorsAnjar Tri Wibowo, M. Fariz Fadillah Mardianto, Riries Rulaningtyas, Satya Candra Wibawa Sakti, Muhammad Fauzul Imron, Rico Ramadhan
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735442610
DOIs
Publication statusPublished - 25 Jan 2022
Event8th International Conference and Workshop on Basic and Applied Science, ICOWOBAS 2021 - Surabaya, Indonesia
Duration: 25 Aug 202126 Aug 2021

Publication series

NameAIP Conference Proceedings
Volume2554
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference8th International Conference and Workshop on Basic and Applied Science, ICOWOBAS 2021
Country/TerritoryIndonesia
CitySurabaya
Period25/08/2126/08/21

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