Work

kpop : a kernel balancing approach for reducing specification assumptions in survey weighting

Year: 2024

Type: article

Source: Journal of the Royal Statistical Society Series A (Statistics in Society)

DOI: 10.1093/jrsssa/qnae082

Authors: Erin Hartman, Chad Hazlett, Ciara Sterbenz

Institutions: University of California, Berkeley, University of California, Los Angeles

Language: English

Topic: Survey Sampling and Estimation Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: closed

Funders: National Institutes of Health, University of California, Los Angeles, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: G2760507634, California Center for Population Research (CCPR) at UCLA

OpenAlex ID: W4402135106

FWCI: 0.987

Cites: 33

Cited by: 3

Related to: 10