Measurement Error Correction and Management in Survey Data – Focusing on Earned Income

Abstract

Survey data are usually constructed through sampling by extracting some subjects from the population of interest. Since we make inferences about the entire population with the survey data, there will be a difference between the sample estimate and the true population value. The difference between the sample estimate and the true population value is defined as an error, which can occur from various causes and situations. This study analyzes the measurement errors that occurr in sample survey data, and proposes two methods(measurement error correction in the linear regression models with continuous outcomes and kernel density estimation for heaped data) for correcting them. In addition, this study proposes a survey data management method that allows production of high-quality data.