Estimasi Parameter Model Regresi Logistik Biner dengan Conditional Maximum Likelihood Estimation pada Data Panel
Keywords:
Human Development Index, Life Expectancy Rate, Expectation of Old School Years, Average Length of Schooling, Conditional Maximum Likelihood EstimationAbstract
Binary logistic regression models can be used on panel data with categorical responses that experience repeated measurements based on time. This study aims to determine the factors that influence the Human Development Index in South Sulawesi Province in 2015-2019. Data were analyzed through binary logistic regression with fixed effect model approach through Conditional Maximum Likelihood Estimation (CMLE) for panel data. The results of this study indicate that the variables that have a significant effect are life expectancy (X1), school length expectancy (X2) and the average length of schooling (X3). Obtained the probability value of districts/cities that have a medium low and medium high human development index with a classification accuracy of 56.25%.
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