caa a22 4500 605519854 CHVBK 20210128100732.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11009-015-9445-8 doi (NATIONALLICENCE)springer-10.1007/s11009-015-9445-8 Bayesian Threshold Regression Model with Random Effects for Recurrent Events [Elektronische Daten] [P. Economou, S. Malefaki, C. Caroni] It is of practical importance to extend time-to-event models in order to be applicable in situations with recurrent events on the same individual or machine. The model proposed here extends in this direction a threshold regression model with random individual effects, in which event times are modeled as realizations of the first hitting times of an underlying Wiener process, leading to Inverse Gaussian distributions of times between events. In our approach, the parameters of the distribution of an event time may depend on features of the process (such as number of previous events and total elapsed time) as well as on measured, possibly time varying, covariates and the individuals' random effects. A Bayesian approach is adopted for model estimation using an improved MCMC algorithm, which guarantees a proper choice of proposal distribution at any step of the hybrid Gibbs sampler when this is required. Model fitting is investigated using simulated data and the model is applied to a set of real data on drug users who made repeated contacts with treatment services. Springer Science+Business Media New York, 2015 Survival analysis nationallicence Recurrent events nationallicence Wiener process nationallicence First hitting time regression nationallicence Inverse Gaussian distribution nationallicence Economou P. Department of Civil Engineering, University of Patras, 26504, Rion-Patras, Greece aut Malefaki S. Department of Mechanical Engineering and Aeronautics, University of Patras, 26504, Rion-Patras, Greece aut Caroni C. Department of Mathematics, School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 157 80, Athens, Greece aut Methodology and Computing in Applied Probability Springer US; http://www.springer-ny.com 17/4(2015-12-01), 871-898 1387-5841 17:4<871 2015 17 11009 https://doi.org/10.1007/s11009-015-9445-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11009-015-9445-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Economou P. Department of Civil Engineering, University of Patras, 26504, Rion-Patras, Greece aut NATIONALLICENCE 700 1- Malefaki S. Department of Mechanical Engineering and Aeronautics, University of Patras, 26504, Rion-Patras, Greece aut NATIONALLICENCE 700 1- Caroni C. Department of Mathematics, School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 157 80, Athens, Greece aut NATIONALLICENCE 773 0- Methodology and Computing in Applied Probability Springer US; http://www.springer-ny.com 17/4(2015-12-01), 871-898 1387-5841 17:4<871 2015 17 11009