White Papers

Using Regression Diagnostics and Clustering Criteria to Uncover ID Errors

Category: Data Management, Networking and Communications

Tags: data

Overview In a large observational study, key patient information was not always recorded accurately at every visit, including the patient identification number, the site, and the date of the visit. Because of the nature of the study, some patients were seen at more than one site the same year (possibly unknown to the other site) or might be seen for some years at one site, drop out, and reappear at the same or a different site some years later. In addition, there are patient ID numbers that appear to be in use by two different individuals simultaneously. With 13 years of data collection and tens of thousands of individuals, the paper needed an efficient way to detect the most obvious of the ID errors.

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Publisher: SAS Institute
File Format: PDF
Date Published: Sep 19, 2008
Format: White Papers
Topics: Diagnostics and Analysis, Data Mining - Analysis

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