Estimating correlations between vaccine clinical trial outcomes
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
| Veröffentlicht in: | Journal of applied statistics. - 1991. - 49(2022), 13 vom: 30., Seite 3392-3413 |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2022
|
| Zugriff auf das übergeordnete Werk: | Journal of applied statistics |
| Schlagworte: | Journal Article 62P10 62P20 62Pxx Applications of statistics clinical trials correlations factor models latent variables maximum likelihood |
| Zusammenfassung: | © 2021 Informa UK Limited, trading as Taylor & Francis Group. We demonstrate how a linear factor model with latent variables can be used to estimate correlations between the outcomes of clinical trials. These correlations are needed for many policy questions of drug/vaccine development (such as calculating the optimal size of financial incentives) and the literature so far has relied on expert opinions. We apply our methodology to the case of vaccines and show that the estimated correlations are highly significant. We also illustrate how the estimated correlations can be used to find the probability of obtaining a successful vaccine out of a certain number of candidates and to determine optimal investment in vaccine development |
|---|---|
| Beschreibung: | Date Revised 05.09.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2021.1949439 |