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- Publisher Website: 10.1080/10543406.2022.2108826
- Scopus: eid_2-s2.0-85135773146
- WOS: WOS:000838647400001
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Article: Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies
| Title | Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies |
|---|---|
| Authors | |
| Keywords | Andersen–Gill model infectious disease non-linear function protective efficacy recurrent events time-varying effect |
| Issue Date | 10-Aug-2022 |
| Publisher | Taylor and Francis Group |
| Citation | Journal of Biopharmaceutical Statistics, 2022, v. 33, n. 2, p. 220-233 How to Cite? |
| Abstract | Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen–Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation. |
| Persistent Identifier | http://hdl.handle.net/10722/331592 |
| ISSN | 2023 Impact Factor: 1.2 2023 SCImago Journal Rankings: 0.812 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Cheung, Yin Bun | - |
| dc.contributor.author | Ma, Xiangmei | - |
| dc.contributor.author | Lam, K F | - |
| dc.contributor.author | Yung, Chee Fu | - |
| dc.contributor.author | Milligan, Paul | - |
| dc.date.accessioned | 2023-09-21T06:57:13Z | - |
| dc.date.available | 2023-09-21T06:57:13Z | - |
| dc.date.issued | 2022-08-10 | - |
| dc.identifier.citation | Journal of Biopharmaceutical Statistics, 2022, v. 33, n. 2, p. 220-233 | - |
| dc.identifier.issn | 1054-3406 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/331592 | - |
| dc.description.abstract | <p>Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen–Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation.<br></p> | - |
| dc.language | eng | - |
| dc.publisher | Taylor and Francis Group | - |
| dc.relation.ispartof | Journal of Biopharmaceutical Statistics | - |
| dc.subject | Andersen–Gill model | - |
| dc.subject | infectious disease | - |
| dc.subject | non-linear function | - |
| dc.subject | protective efficacy | - |
| dc.subject | recurrent events | - |
| dc.subject | time-varying effect | - |
| dc.title | Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1080/10543406.2022.2108826 | - |
| dc.identifier.scopus | eid_2-s2.0-85135773146 | - |
| dc.identifier.volume | 33 | - |
| dc.identifier.issue | 2 | - |
| dc.identifier.spage | 220 | - |
| dc.identifier.epage | 233 | - |
| dc.identifier.eissn | 1520-5711 | - |
| dc.identifier.isi | WOS:000838647400001 | - |
| dc.identifier.issnl | 1054-3406 | - |