frailtyHL-package: H-likelihood Approach for Frailty Models

In frailtyHL: Frailty Models via Hierarchical Likelihood

Description

The frailtyHL package fits frailty models which are Cox's proportional hazards models incorporating random effects. The function implements the h-likelihood estimation procedures. For the frailty distribution lognormal and gamma are allowed. The h-likelihood uses the Laplace approximation when the numerical integration is intractable, giving a statistically efficient estimation in frailty models. (Ha, Lee and Song, 2001; Ha and Lee, 2003, 2005; Lee, Nelder and Pawitan, 2017; Ha, Jeong and Lee, 2017). This package handles various random-effect survival models such as time-dependent frailties, competing-risk frailty models, AFT random-effect models, and joint modelling of linear mixed models and frailty models. It also provides penalized variable-selection procedures (LASSO, SCAD and HL).

Details

Package:	frailtyHL
Type:	Package
Version:	2.1
Date:	2016-09-19
License:	Unlimited
LazyLoad:	yes

This is version 2.2 of the frailtyHL package.

Author(s)

Il Do Ha, Maengseok Noh, Jiwoong Kim, Youngjo Lee

Maintainer: Maengseok Noh <[e-mail]>

References

Ha, I. D. and Lee, Y. (2003). Estimating frailty models via Poisson Hierarchical generalized linear models. Journal of Computational and Graphical Statistics, 12, 663-681.

Ha, I. D. and Lee, Y. (2005). Comparison of hierarchical likelihood versus orthodox best linear unbiased predictor approaches for frailty models. Biometrika, 92, 717-723.

Ha, I. D., Lee, Y. and Song, J. K. (2001). Hierarchical likelihood approach for frailty models. Biometrika, 88, 233-243.

Ha, I. D., Jeong, J. and Lee, Y. (2017). Statistical modelling of survival data with random effects. Springer.

Lee, Y., Nelder, J. A. and Pawitan, Y. (2017). Generalised linear models with random effects: unified analysis via h-likelihood. 2nd Edition. Chapman and Hall: London.

Examples

data(kidney)
kidney_g12<-frailtyHL(Surv(time,status)~sex+age+(1|id),kidney)

Example output

Loading required package: Matrix
Loading required package: survival
Loading required package: cmprsk
iteration :  
          46 
convergence :  
   7.61095e-07 
[1] "converged"
[1] "Results from the log-normal frailty model"
[1] "Number of data : "
[1] 76
[1] "Number of event : "
[1] 58
[1] "Model for conditional hazard : "
Surv(time, status) ~ sex + age + (1 | id)
[1] "Method : HL(0,1)"
[1] "Estimates from the mean model"
     Estimate Std. Error t-value  p-value
sex -1.380431    0.43082 -3.2042 0.001354
age  0.004885    0.01209  0.4041 0.686123
[1] "Estimates from the dispersion model"
   Estimate Std. Error
id   0.5345     0.3384
      -2h0  -2*hp -2*p_b,v(hp)
[1,] 330.4 390.77       371.54
       cAIC  pAIC   rAIC
[1,] 362.46 370.7 373.54

frailtyHL documentation built on Dec. 1, 2019, 1:25 a.m.