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

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

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…