The article introduces a new statistical test and optimal estimation method for dealing with missing data in research. The researchers developed these methods to handle situations where the missing data is not random, which can complicate analysis. By using these new techniques, researchers can estimate population parameters like the average income more accurately without needing to make additional assumptions about the data. The methods were tested using real-world data from a Korean labor and income survey, showing promising results compared to existing methods.