Evaluating Methods for Imputing Race and Ethnicity in Electronic Health Record Data
BISG imputation may provide a more accurate racial and ethnic classification than single or multiple imputation using anonymized covariates, particularly if the missing data mechanism is MNAR. Descriptive studies of disease burden may not be sensitive to methods for imputing missing data.
Authors
- Mark G. Weiner (ORCID: https://orcid.org/0000-0001-5586-9940)
- John A. Dodson (ORCID: https://orcid.org/0000-0003-0163-3013)
- Samrachana Adhikari (ORCID: https://orcid.org/0000-0001-9954-5999)
- Sarah Conderino (ORCID: https://orcid.org/0000-0003-1762-9262)
- Jasmin Divers (ORCID: https://orcid.org/0000-0003-0120-7620)
- Lorna E. Thorpe (ORCID: https://orcid.org/0000-0002-5535-2674)
Institutions
- Long Island University (US)
- Cornell University (US)
- Weill Cornell Medicine (US)
- New York University (US)
Publication Details
- Journal
- Health Services Research
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1111/1475-6773.14649
- Citations
- 1
- Primary Topic
- Global Cancer Incidence and Screening
- Type
- article
- Field-Weighted Citation Impact
- 1.05
Funders
- National Institutes of Health
- National Institute on Aging