WL01: Advancing Record Linkage: Better Algorithms, Better Estimation Methods

Music City Center 

Linking data from various sources is essential for generating accurate statistics and assessing the impact of interventions. With declining survey response rates, rapid technological advancements, and the growing volume of data collected by different organizations, the need for effective data linkage has never been greater. Linkage algorithms aim to integrate information from public and private datasets to enhance official statistics, improve disease outbreak prediction, support policy monitoring, and facilitate comparative effectiveness research. However, a major challenge arises when unique identifying information is unavailable across datasets, because of privacy concerns. This roundtable will explore current challenges in linking data without unique identifiers and discuss potential algorithmic advancements to improve computational efficiency as well as accuracy of the linkage process. In addition, we will discuss possible advancement in the analysis of link datasets.

Record Linkage

Entity Resolution

Error Propagation

Computational Algorithms

Software Availability 

Government Statistics Section