Where are our false positives?

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dc.contributor.authorPerezgonzalez J
dc.date.accessioned2023-10-24T00:53:38Z
dc.date.available2022-05-03
dc.date.available2023-10-24T00:53:38Z
dc.date.issued2022-05-03
dc.description.abstractIn our current regime of COVID-19 testing, a question seems not to be asked: Are we inferring the best we can from our results? Or, put differently, are we testing with severity? This study thus explore the proportion of expected positives and negative cases, with an especial focus on estimating false positives in isolation and estimating false (or unknown) negatives in the remaining population. Both seems to have been chiefly ignored by Government health policy.
dc.identifierhttps://osf.io/7pshw/
dc.identifier.citation2022
dc.identifier.doi10.31219/osf.io/7pshw
dc.identifier.elements-id454557
dc.identifier.harvestedMassey_Dark
dc.identifier.urihttp://hdl.handle.net/10179/20370
dc.publisherOSF Preprints
dc.publisher.urihttps://osf.io/7pshw/
dc.relation.urihttps://osf.io/7pshw/
dc.rights(c) The Author
dc.subjectBayesian statistics
dc.subjectCOVID-19
dc.subjectStatistical inference
dc.subjectSeverity
dc.titleWhere are our false positives?
dc.typeinternet
pubs.notesNot known
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/Massey Business School
pubs.organisational-group/Massey University/Massey Business School/School of Aviation
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