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- W4315705841 abstract "Forecasting recruitments is a key component of the monitoring phase of multicenter studies. One of the most popular techniques in this field is the Poisson-Gamma recruitment model, a Bayesian technique built on a doubly stochastic Poisson process. This approach is based on the modeling of enrollments as a Poisson process where the recruitment rates are assumed to be constant over time and to follow a common Gamma prior distribution. However, the constant-rate assumption is a restrictive limitation that is rarely appropriate for applications in real studies. In this paper, we illustrate a flexible generalization of this methodology which allows the enrollment rates to vary over time by modeling them through B-splines. We show the suitability of this approach for a wide range of recruitment behaviors in a simulation study and by estimating the recruitment progression of the Canadian Co-infection Cohort (CCC)." @default.
- W4315705841 created "2023-01-12" @default.
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- W4315705841 date "2023-01-09" @default.
- W4315705841 modified "2023-10-01" @default.
- W4315705841 title "A time-dependent Poisson-Gamma model for recruitment forecasting in multicenter studies" @default.
- W4315705841 doi "https://doi.org/10.48550/arxiv.2301.03710" @default.
- W4315705841 hasPublicationYear "2023" @default.
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