ArticleScience advances2022
Addressing census data problems in race imputation via fully Bayesian Improved Surname Geocoding and name supplements.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Enhancing Evidence Generation by Linking Randomized Clinical Trials to Real-World Data: The INVESTED-Medicare Linkage Study.Clinical pharmacology and therapeutics · 2026Article
- Geographic Availability and Use of Medications for Opioid Use Disorder Among Medicaid Enrollees.JAMA health forum · 2026Article
- Evaluating Methods for Imputing Race and Ethnicity in Electronic Health Record Data.Health services research · 2025Article
- Enabling disaggregation of Asian American subgroups: a dataset of Wikidata names for disparity estimation.Scientific data · 2025Article
- Determinants of utilization of infertility services by race and ethnicity in a state with a comprehensive infertility mandate.Fertility and sterility · 2025Article
- Addressing discretization-induced bias in demographic prediction.PNAS nexus · 2025Article
- Inferring Unknown Race in Central Cancer Registries.Journal of registry management · 2025Article
- Loss to Follow-Up in Patients With Proliferative Diabetic Retinopathy or Diabetic Macular Edema.JAMA network open · 2024Article
- The Evolution of Pediatric Spine Surgery: A Bibliometric Analysis of Publications From 1902 to 2023.Neurosurgery practice · 2024Article
- American local government elections database.Scientific data · 2023Article
- Receipt and duration of buprenorphine treatment during pregnancy and postpartum periods in a national privately-insured cohort.Drug and alcohol dependence reports · 2023Article
- Race and ethnicity data for first, middle, and surnames.Scientific data · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction of individuals' race and ethnicity plays an important role in studies of racial disparity. Bayesian Improved Surname Geocoding (BISG), which relies on detailed census information, has emerged as a leading methodology for this prediction task. Unfortunately, BISG suffers from two data problems. First, the census often contains zero counts for minority groups in the locations where members of those groups reside. Second, many surnames-especially those of minorities-are missing from the census data. We introduce a fully Bayesian BISG (fBISG) methodology that accounts for census measurement error by extending the naïve Bayesian inference of the BISG methodology. We also use additional data on last, first, and middle names taken from the voter files of six Southern states where self-reported race is available. Our empirical validation shows that the fBISG methodology and name supplements substantially improve the accuracy of race imputation, especially for racial minorities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.