{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Gao F"],"funding":["NIAID NIH HHS","National Institutes of Health","NIH HHS"],"pagination":["1446-1461"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8918003"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["41(8)"],"pubmed_abstract":["Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers have sought alternative strategies. Recency test methods use biomarker profiles of HIV-infected subjects in a cross-sectional sample to infer whether they are \"recently\" infected and to estimate incidence in the population. Two main estimators have been used in practice: one that assumes a recency test is perfectly specific, and another that allows for false-recent results. To date, these commonly used estimators have not been rigorously studied with respect to their assumptions and statistical properties. In this article, we present a theoretical framework with which to understand these estimators and interrogate their assumptions, and perform a simulation study and data analysis "],"journal":["Statistics in medicine"],"pubmed_title":["Statistical considerations for cross-sectional HIV incidence estimation based on recency test."],"pmcid":["PMC8918003"],"funding_grant_id":["R56 AI143418","S10OD028685","S10 OD028685"],"pubmed_authors":["Bannick M","Gao F"],"additional_accession":[]},"is_claimable":false,"name":"Statistical considerations for cross-sectional HIV incidence estimation based on recency test.","description":"Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers have sought alternative strategies. Recency test methods use biomarker profiles of HIV-infected subjects in a cross-sectional sample to infer whether they are \"recently\" infected and to estimate incidence in the population. Two main estimators have been used in practice: one that assumes a recency test is perfectly specific, and another that allows for false-recent results. To date, these commonly used estimators have not been rigorously studied with respect to their assumptions and statistical properties. In this article, we present a theoretical framework with which to understand these estimators and interrogate their assumptions, and perform a simulation study and data analysis ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Apr","modification":"2025-04-21T22:52:23.876Z","creation":"2025-04-05T19:00:02.835Z"},"accession":"S-EPMC8918003","cross_references":{"pubmed":["34984710"],"doi":["10.1002/sim.9296"]}}