post_frailty.AdPaik {TimeDepFrail} | R Documentation |
Posterior frailty estimates and variances for the 'Adapted Paik et al.'s Model'
Description
Function for computing the posterior frailty estimates and variances of the time-dependent shared frailty Cox model.
Recalling the structure of the frailty Z_{jk} = \alpha_j + \epsilon_{jk}, \forall j,k
as being composed by the sum
of two independent gamma distributions:
-
\alpha_j \sim gamma(\mu_1/\nu, 1/\nu), \forall j
-
\epsilon_{jk} \sin gamma(\mu_2/\gamma_k, 1/\gamma_k), \forall j,k
the posterior distribution of both terms is still a gamma with different mean and variance and the posterior frailty estimate corresponds to the 'empirical Bayes estimate', that is the previous mentioned posterior mean.
Usage
post_frailty.AdPaik(optimal_params, dataset, time_to_event, centre, time_axis)
Arguments
optimal_params |
Optimal parameters estimated by maximizing the log-likelihood function, through the constraint multi-dimensional optmization method. |
dataset |
Dataset containing all the covariates/regressors. |
time_to_event |
Time-instant, in the follow-up, in which an individual faces the event or fails. If an individual does not face the event in the follow-up, then the time-instant must assume a default value. |
centre |
Individual group/cluster membership. |
time_axis |
Temporal domain. |
Value
S3 object of class 'PF.AdPaik' composed of two elements of different class:
PosteriorFrailtyEst: S3 object of class 'PFE.AdPaik'.
PosteriorFrailtyVar: S3 object of class 'PFV.AdPaik'.