Best Regression Model Selection for Factors Affecting Life Expectancy in Indonesian Provinces in 2024

Muhammad Zulfadhli

doi:10.54065/likelihood.1123

Authors

Muhammad Zulfadhli Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.54065/likelihood.1123

Keywords:

Backward Elimination, Forward Elimination, Multiple Linear Regression, Stepwise Selection, Life Expectancy

Abstract

Life expectancy reflects the welfare and quality of life of the population. BPS data shows an increase in Indonesia's life expectancy from 73.39 years to 74.15 years (+0.298%). Factors that are thought to influence this include average net salary, expected length of schooling, poverty severity index, and GRDP. The analysis was conducted using multiple linear regression, then the best model was selected using Forward Elimination, Backward Elimination, and Stepwise Selection. This study used secondary data obtained from publications and BPS statistical tables, all of which had a ratio measurement scale. There are differences in life expectancy between provinces, as well as high economic inequality. There are no indications of multicollinearity. The best model includes expected years of schooling and GRDP with residuals that meet the assumptions of normality, independence, and homoscedasticity. The model is not yet adequate because it can only explain less than half of the variability in life expectancy in Indonesia in 2024.

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