130 related articles for article (PubMed ID: 38908745)
1. The time-dependent Poisson-gamma model in practice: Recruitment forecasting in HIV trials.
Turchetta A; Moodie EEM; Stephens DA; Savy N; Moodie Z
Contemp Clin Trials; 2024 Jun; ():107607. PubMed ID: 38908745
[TBL] [Abstract][Full Text] [Related]
2. A time-dependent Poisson-Gamma model for recruitment forecasting in multicenter studies.
Turchetta A; Savy N; Stephens DA; Moodie EEM; Klein MB
Stat Med; 2023 Oct; 42(23):4193-4206. PubMed ID: 37491664
[TBL] [Abstract][Full Text] [Related]
3. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
4. Modeling time-varying recruitment rates in multicenter clinical trials.
Perperoglou A; Zhang Y; Kipourou DK
Biom J; 2023 Aug; 65(6):e2100377. PubMed ID: 36287068
[TBL] [Abstract][Full Text] [Related]
5. Predictive event modelling in multicenter clinical trials with waiting time to response.
Anisimov VV
Pharm Stat; 2011; 10(6):517-22. PubMed ID: 22140055
[TBL] [Abstract][Full Text] [Related]
6. Using Poisson-gamma model to evaluate the duration of recruitment process when historical trials are available.
Minois N; Lauwers-Cances V; Savy S; Attal M; Andrieu S; Anisimov V; Savy N
Stat Med; 2017 Oct; 36(23):3605-3620. PubMed ID: 28608361
[TBL] [Abstract][Full Text] [Related]
7. Standardized metrics can reveal region-specific opportunities in community engagement to aid recruitment in HIV prevention trials.
Broder GB; Lucas JP; Davis J; Wallace SE; Luthuli N; Baepanye K; White RR; Bolton M; Blanchette C; Andrasik MP
PLoS One; 2020; 15(9):e0239276. PubMed ID: 32941520
[TBL] [Abstract][Full Text] [Related]
8. surrosurv: An R package for the evaluation of failure time surrogate endpoints in individual patient data meta-analyses of randomized clinical trials.
Rotolo F; Paoletti X; Michiels S
Comput Methods Programs Biomed; 2018 Mar; 155():189-198. PubMed ID: 29512498
[TBL] [Abstract][Full Text] [Related]
9. Recruitment prediction for multicenter clinical trials based on a hierarchical Poisson-gamma model: Asymptotic analysis and improved intervals.
Mountain R; Sherlock C
Biometrics; 2022 Jun; 78(2):636-648. PubMed ID: 33604911
[TBL] [Abstract][Full Text] [Related]
10. Interim recruitment prediction for multi-center clinical trials.
Urbas S; Sherlock C; Metcalfe P
Biostatistics; 2022 Apr; 23(2):485-506. PubMed ID: 32978616
[TBL] [Abstract][Full Text] [Related]
11. How to deal with the Poisson-gamma model to forecast patients' recruitment in clinical trials when there are pauses in recruitment dynamic?
Minois N; Savy S; Lauwers-Cances V; Andrieu S; Savy N
Contemp Clin Trials Commun; 2017 Mar; 5():144-152. PubMed ID: 29740630
[TBL] [Abstract][Full Text] [Related]
12. Enrollment Forecast for Clinical Trials at the Planning Phase with Study-Level Historical Data.
Yu M; Zhong S; Xing Y; Wang L
Ther Innov Regul Sci; 2024 Jan; 58(1):42-52. PubMed ID: 37713098
[TBL] [Abstract][Full Text] [Related]
13. Modelling, prediction and adaptive adjustment of recruitment in multicentre trials.
Anisimov VV; Fedorov VV
Stat Med; 2007 Nov; 26(27):4958-75. PubMed ID: 17639505
[TBL] [Abstract][Full Text] [Related]
14. Motivation, recruitment, and screening of volunteers for a phase I/II HIV preventive vaccine trial in Thailand.
Jenkins RA; Chinaworapong S; Morgan PA; Ruangyuttikarn C; Sontirat A; Chiu J; Michael RA; Nitayaphan S; Khamboonruang C
J Acquir Immune Defic Syndr Hum Retrovirol; 1998 Jun; 18(2):171-7. PubMed ID: 9637582
[TBL] [Abstract][Full Text] [Related]
15. A trial platform to assess approved SARS-CoV-2 vaccines in immunocompromised patients: first sub-protocol for a pilot trial comparing the mRNA vaccines Comirnaty® and COVID-19 mRNA Vaccine Moderna®.
Speich B; Chammartin F; Smith D; Stoeckle MP; Amico P; Eichenberger AL; Hasse B; Schuurmans MM; Müller T; Tamm M; Dickenmann M; Abela IA; Trkola A; Hirsch HH; Manuel O; Cavassini M; Hemkens LG; Briel M; Mueller NJ; Rauch A; Günthard HF; Koller MT; Bucher HC; Kusejko K;
Trials; 2021 Oct; 22(1):724. PubMed ID: 34674742
[TBL] [Abstract][Full Text] [Related]
16. A MATLAB toolbox to fit and forecast growth trajectories using phenomenological growth models: Application to epidemic outbreaks.
Chowell G; Bleichrodt A; Dahal S; Tariq A; Roosa K; Hyman JM; Luo R
Res Sq; 2023 Apr; ():. PubMed ID: 37034746
[TBL] [Abstract][Full Text] [Related]
17. The Incidence Patterns Model to Estimate the Distribution of New HIV Infections in Sub-Saharan Africa: Development and Validation of a Mathematical Model.
Bórquez A; Cori A; Pufall EL; Kasule J; Slaymaker E; Price A; Elmes J; Zaba B; Crampin AC; Kagaayi J; Lutalo T; Urassa M; Gregson S; Hallett TB
PLoS Med; 2016 Sep; 13(9):e1002121. PubMed ID: 27622516
[TBL] [Abstract][Full Text] [Related]
18. Gaussian process emulation to improve efficiency of computationally intensive multidisease models: a practical tutorial with adaptable R code.
Sawe SJ; Mugo R; Wilson-Barthes M; Osetinsky B; Chrysanthopoulou SA; Yego F; Mwangi A; Galárraga O
BMC Med Res Methodol; 2024 Jan; 24(1):26. PubMed ID: 38281017
[TBL] [Abstract][Full Text] [Related]
19. SpatialWavePredict: a tutorial-based primer and toolbox for forecasting growth trajectories using the ensemble spatial wave sub-epidemic modeling framework.
Chowell G; Tariq A; Dahal S; Bleichrodt A; Luo R; Hyman JM
BMC Med Res Methodol; 2024 Jun; 24(1):131. PubMed ID: 38849766
[TBL] [Abstract][Full Text] [Related]
20. GrowthPredict: A toolbox and tutorial-based primer for fitting and forecasting growth trajectories using phenomenological growth models.
Chowell G; Bleichrodt A; Dahal S; Tariq A; Roosa K; Hyman JM; Luo R
Sci Rep; 2024 Jan; 14(1):1630. PubMed ID: 38238407
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
