Addressing bias in preterm birth research: The role of advanced imputation techniques for missing race and ethnicity in perinatal health data

Scroggins, J. K., Hulchafo, I. I., Topaz, M., Cato, K., & Barcelona, V. (2024). Addressing bias in preterm birth research: The role of advanced imputation techniques for missing race and ethnicity in perinatal health data. Annals of Epidemiology, 94, 120–126. https://doi.org/10.1016/j.annepidem.2024.05.003
Authors:
Jihye Kim Scroggins
Ismael Ibrahim Hulchafo
Maxim Topaz
Kenrick Cato
Veronica Barcelona
Affiliated Authors:
Jihye Kim Scroggins
Ismael Ibrahim Hulchafo
Maxim Topaz
Veronica Barcelona
Columbia Affiliation:
Subjects:
Premature Birth (MeSH)
Bayes Theorem (MeSH)
Bias (MeSH)
Electronic Health Records (MeSH)
Ethnicity (MeSH)
Author Keywords:
electronic health records
health disparities
missing data
preterm birth
race and ethnicity
elink
Publication Type:
Article
Unique ID:
10.1016/j.annepidem.2024.05.003
PMID:
38734192
DOI:
10.1016/j.annepidem.2024.05.003
Journal:
Annals of Epidemiology
Publication Date:
Data Source:
PubMed
Source Link:
View PubMed Record
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Record Created: