activity
20162025
most citedEfficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data

2 citations · 3 across the 4 of their papers we have counts for

collaborators
Showing stat.COShow all

1 paper · 1 filter

stat.CO2023★ 2 cited

Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data

P. Miranda Afonso, D. Rizopoulos, A. K. Palipana +4

The joint modeling of longitudinal and time-to-event outcomes has become a popular tool in follow-up studies. However, fitting Bayesian joint models to large datasets, such as pati…