Inflation of type I error rates due to differential misclassification in EHR‐derived outcomes: Empirical illustration using breast cancer recurrence
Author:
Affiliation:
1. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of MedicineUniversity of Pennsylvania Philadelphia Pennsylvania USA
2. Kaiser Permanente Washington Health Research InstituteKaiser Permanente Washington Seattle WA USA
Funder
National Cancer Institute
National Institute of Allergy and Infectious Diseases
U.S. National Library of Medicine
American Cancer Society
Publisher
Wiley
Subject
Pharmacology (medical),Epidemiology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/pds.4680
Reference17 articles.
1. Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research
2. Strategies for handling missing data in electronic health record derived data;Wells BJ;EGEMS (Wash DC),2013
3. Defining and measuring completeness of electronic health records for secondary use
4. Bias and efficiency loss due to misclassified responses in binary regression
5. Logistic Regression When the Outcome Is Measured with Uncertainty
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