A Bayesian approach to statistical matching using the national health screening data

Abstract

The problem of missing data that complicates the data analysis process, is an inevitable phenomenon in various studies. Statistical matching using existing data or information can solve this problem. Many studies have been conducted on statistical matching. This includes linear regression models and nonparametric methods. However, the aforementioned methods may not perform well in small sample problems. This study attempts to address this issue from a Bayesian perspective. In particular, we verify the performance of our Bayesian-based statistical matching method in small sample problems. We use the real observed data from the National Health Screening Data to compare the proposed model with other existing methods.