Estimating the number of persons with HIV in jails via web scraping and record linkage

Bonnie E. Shook‐Sa, Michael G. Hudgens, Andrew L. Kavee and David L. Rosen

Journal of the Royal Statistical Society Series A, 2022, vol. 185, issue S2, S270-S287

Abstract: This paper presents methods to estimate the number of persons with HIV in North Carolina jails by applying finite population inferential approaches to data collected using web scraping and record linkage techniques. Administrative data are linked with web‐scraped rosters of incarcerated persons in a non‐random subset of counties. Outcome regression and calibration weighting are adapted for state‐level estimation. Methods are compared in simulations and are applied to data from the US state of North Carolina. Outcome regression yielded more precise inference and allowed for county‐level estimates, an important study objective, while calibration weighting exhibited double robustness under misspecification of the outcome or weight model.

Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/rssa.12909

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:185:y:2022:i:s2:p:s270-s287

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-985X

Access Statistics for this article

Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples

More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().