We use different machine learning models to predict the life expectancy of individuals from the longitudinal Health and Retirement Survey. This code was produced by Ray Carpenter, Jason Jiminez, and Nick Kirkman for Econ 573 - Machine Learning and Econometrics. The Rand Health and Retirement Study used was conducted from 1992 to 2020 and followed individuals nearing and after retirement. Through different models, we were able to analyze different aspects of aging in this population. This repository contains the code to bring the data from the Rand HRS Longitudinal Dataset, to cleaning, and to produce the findings in the paper.
- Full Paper: https://github.com/RayCarpenterIII/Machine-Learning-Applications-for-Life-Expectancy-Prediction/blob/main/Machine%20Learning%20Applications%20for%20Life%20Expectancy%20Predictions%20-%20Carpenter%2C%20Jiminez%2C%20Kirkman.pdf
- Raw Data: https://hrsdata.isr.umich.edu/data-products/rand-hrs-longitudinal-file-2020