Data integration using statistical matching techniques: A review

Document Type

Article

Publication Date

Winter 11-26-2021

Abstract

In the era of data revolution, availability and presence of data is a huge wealth that has to be utilized. Instead of making new surveys, bene t can be made from data that already exists. As enormous amounts of data become available, it is becoming essential to undertake research that involves integrating data from multiple sources in order to make the best use out of it. Statistical Data Integration (SDI) is the statistical tool for considering this issue. SDI can be used to integrate data les that have common units, and it also allows to merge unrelated les that don't share any common units, depending on the input data. The convenient method of data integration is determined according to the nature of the input data. SDI has two main methods, Record Linkage (RL) and Statistical Matching (SM). SM techniques typically aim to achieve a complete data le from di erent sources which do not contain the same units. This paper aims at giving a complete overview of existing SM methods in order to provide a uni ed summary of various SM techniques along with their drawbacks. Points for future research are suggested at the end of this paper.

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