Penerapan Metode Stepwise dan Dominance Analysis Pada Regresi Logistik Biner (Studi Kasus: Data Hipertensi Di Indonesia)

Abstract

Binary logistic regression is a method to describe the relationship between response variable that has two categories and one or more predictor variables. One of methods that can be used to obtain best model in logistic regression is stepwise. Stepwise method is a method that sets  and  as criteria to build model. Dominance analysis is used in this research to determine the importance rank of predictor variables by comparing the coefficient of determination  value before and after the predictor variable entered the model. Binary logistic regression can be used to find the relationship between hypertension and the factor risks. This study aims to obtain best model and to obtain the importace rank each predictor variable of binary logistic regression on data of hypertension in Indonesia. The result of this study shows that best model which is obtained is model with predictor variable of Heart Problems, High Cholesterol, Kidney Disease, Imperfect Vision, Breathlessness, and Nausea/ Vomitting. According to the value of  McFadden, predictor variable of High Cholesterol infests first rank in the importance of predictor variable or gives the greatest contributions in explaining variety of Status of Hypertension than other predictor variables.Binary logistic regression is a method to describe the relationship between response variable that has two categories and one or more predictor variables. One of methods that can be used to obtain best model in logistic regression is stepwise. Stepwise method is a method that sets  and  as criteria to build model. Dominance analysis is used in this research to determine the importance rank of predictor variables by comparing the coefficient of determination  value before and after the predictor variable entered the model. Binary logistic regression can be used to find the relationship between hypertension and the factor risks. This study aims to obtain best model and to obtain the importace rank each predictor variable of binary logistic regression on data of hypertension in Indonesia. The result of this study shows that best model which is obtained is model with predictor variable of Heart Problems, High Cholesterol, Kidney Disease, Imperfect Vision, Breathlessness, and Nausea/ Vomitting. According to the value of  McFadden, predictor variable of High Cholesterol infests first rank in the importance of predictor variable or gives the greatest contributions in explaining variety of Status of Hypertension than other predictor variables.