On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
The shared frailty model and the power for heterogeneity tests in multicenter trials
Computational Statistics & Data Analysis
Simplified modeling strategies for surrogate validation with multivariate failure-time data
Computational Statistics & Data Analysis
A simulation procedure based on copulas to generate clustered multi-state survival data
Computer Methods and Programs in Biomedicine
On a convergent stochastic estimation algorithm for frailty models
Statistics and Computing
Bayesian variable selection under the proportional hazards mixed-effects model
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
Proportional hazards models with multivariate random effects (frailties) acting multiplicatively on the baseline hazard are a topic of intensive research. Several estimation procedures have been proposed to deal with this type of models. Four procedures used to fit these models are compared in two real-life datasets and in a simulation study. The performance of the four methods is investigated in terms of the bias of point estimates, their empirical variability and the bias of the estimation of the variability.