Subset Best Method Regression Analysis with Cp Mallows Statistics on Factors Affecting Life Expectancy

• Main Authors: HARDIAN BIMANTO, 101611123034, Hari Basuki Notobroto, -, Soenarnatalina Melaniani, -
• Format: Article PeerReviewed
• Language: English; English; English
• Published: Humanistic Network for Science and Technology 2022
• Subjects: R Medicine
• Online Access: https://repository.unair.ac.id/125003/1/C135_Artikel.pdf; https://repository.unair.ac.id/125003/2/C135_Turnitin.pdf; https://repository.unair.ac.id/125003/3/C135_Validasi.pdf; https://repository.unair.ac.id/125003/; https://heanoti.com/index.php/hn/article/view/858; http://dx.doi.org/10.33846/hn60306
• Institution: Universitas Airlangga

One method used in the multiple linear regression model is the best subset using Cp Mallows statistics. The best subset begins by combining independent variables to describe the dependent variable. Select a combination with a high coefficient of determination and a low Cp value. The purpose of this study was to apply the best subset method of Cp Mallows statistics to obtain multiple linear regression models of factors that affect life expectancy. This survey was a secondary data survey using data from Health Profiles published in 2016 in East Java. Data from 38 cities with dependent variables were life expectancy and independent variables such as diarrhea prevalence, dengue prevalence, healthy homes, clean and healthy living behavior, and average school hours. The results showed that the coefficient of determination was 69.7% and the Cp value was 3.9 for the three combinations of diarrhea prevalence, healthy family, and average school hours.