Autor: |
Turchetta, Armando, Savy, Nicolas, Stephens, David A., Moodie, Erica E. M., Klein, Marina B. |
Rok vydání: |
2023 |
Předmět: |
|
Druh dokumentu: |
Working Paper |
Popis: |
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). |
Databáze: |
arXiv |
Externí odkaz: |
|