General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv. The R package frailtySurv for simulating and fitting semi-parametric shared frailty models is introduced. frailtySurv implements semi-parametric consistent estimators for a variety of frailty distributions, including gamma, log-normal, inverse Gaussian and power variance function, and provides consistent estimators of the standard errors of the parameters’ estimators. The parameters’ estimators are asymptotically normally distributed, and therefore statistical inference based on the results of this package, such as hypothesis testing and confidence intervals, can be performed using the normal distribution. Extensive simulations demonstrate the flexibility and correct implementation of the estimator. Two case studies performed with publicly-available datasets demonstrate applicability of the package. In the Diabetic Retinopathy Study, the onset of blindness is clustered by patient, and in a large hard drive failure dataset, failure times are thought to be clustered by the hard drive manufacturer and model.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Theodor Balan; Hein Putter: frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models (2019) not zbMATH
- John Monaco; Malka Gorfine; Li Hsu: General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv (2018) not zbMATH
- John V. Monaco, Malka Gorfine, Li Hsu: General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv (2017) arXiv