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The effect of data cleaning on record linkage quality
Sean M Randall1, Anna M Ferrante, James H Boyd
1Centre for Data Linkage, Curtin Health Innovation Research Institute, Curtin University, Perth, WA GPO U1987, Australia. sean.randall@curtin.edu.au
BMC Medical Informatics and Decision Making
|June 7, 2013
Summary
Data cleaning techniques have minimal impact on record linkage quality. Overly aggressive cleaning can decrease accuracy by increasing false matches, highlighting the need for careful application.
Area of Science:
- Data Science
- Information Science
- Computer Science
Background:
- Record linkage relies on data cleaning and standardization for high-quality links.
- These techniques are common in software but their impact on linkage quality is under-published.
Purpose of the Study:
- To investigate the impact of data cleaning on record linkage quality.
- To evaluate the effectiveness of various data cleaning techniques.
Main Methods:
- Applied data cleaning techniques to synthetic and administrative datasets.
- Assessed linkage quality using pairwise F-measure before and after cleaning.
Main Results:
- Data cleaning had minimal effect on overall linkage quality.
- Heavy cleaning led to a decrease in linkage quality.
- Decreased quality resulted from reduced data variability, increasing both correct and incorrect matches, with false matches dominating.
Conclusions:
- Data cleaning techniques demonstrate minimal effect on record linkage quality.
- Caution is advised during the data cleaning process to avoid unintended consequences.
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