Impact of linkage level on inferences from big data analyses in health and medical research: an empirical study.

ABSTRACT:

Background

Linkage errors that occur according to linkage levels can adversely affect the accuracy and reliability of analysis results. This study aimed to identify the differences in results according to personally identifiable information linkage level, sample size, and analysis methods through empirical analysis.

Methods

The difference between the results of linkage in directly identifiable information (DII) and indirectly identifiable information (III) linkage levels was set as III linkage based on name, date of birth, and sex and DII linkage based on resident registration number. The datasets linked at each level were named as database_III (DB_III) and database_DII (DB_DII), respectively. Considering the analysis results of the DI

SUBMITTER: Lee B 

PROVIDER: S-EPMC11234607 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature