| dc.contributor.author | Perezgonzalez, J | en_US |
| dc.date.available | 2022-05-03 | en_US |
| dc.date.issued | 2022-05-03 | en_US |
| dc.identifier | https://osf.io/7pshw/ | en_US |
| dc.identifier.citation | 2022 | en_US |
| dc.description.abstract | In 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. | en_US |
| dc.publisher | OSF Preprints | en_US |
| dc.relation.uri | https://osf.io/7pshw/ | en_US |
| dc.rights | (c) The Author | en_US |
| dc.subject | Bayesian statistics | en_US |
| dc.subject | COVID-19 | en_US |
| dc.subject | Statistical inference | en_US |
| dc.subject | Severity | en_US |
| dc.title | Where are our false positives? | en_US |
| dc.type | Internet Publication | |
| dc.identifier.doi | 10.31219/osf.io/7pshw | en_US |
| dc.identifier.elements-id | 454557 | |
| pubs.organisational-group | /Massey University | |
| pubs.organisational-group | /Massey University/Massey Business School | |
| pubs.organisational-group | /Massey University/Massey Business School/School of Aviation | |
| dc.identifier.harvested | Massey_Dark | |
| pubs.notes | Not known | en_US |
| dc.publisher.uri | https://osf.io/7pshw/ | en_US |
