建议你先看一下这本书:

Modeling Survival Data Using Frailty Models

chap 2. Some Parametric Methods
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . .     19
2.2 Exponential Distribution . . . . . . . . . . . . . . . . . . . 20
2.3 Weibull Distribution . . . . . . . . . . . . . . . . . . . . .   21
2.4 Extreme Value Distributions . . . . . . . . . . . . . . . . 23
2.5 Lognormal . . . . . . . . . . . . . . . . . . . . . . . . . .     25
2.6 Gamma . . . . . . . . . . . . . . . . . . . . . . . . . . . .     26
2.7 Loglogistic . . . . . . . . . . . . . . . . . . . . . . . . .       29
2.8 Maximum Likelihood Estimation . . . . . . . . . . . . . 30
2.9 Parametric Regression Models

chap 6. Estimation Methods for Shared Frailty Models
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . .        105
6.2 Inference for the Shared Frailty Model . . . . . . . . . .  106
6.3 The EM Algorithm . . . . . . . . . . . . . . . . . . . . . . .    108
6.4 The Gamma Frailty Model . . . . . . . . . . . . . . . . . . .  110
6.5 The Positive Stable Frailty Model . . . . . . . . . . . . . .  111
6.6 The Lognormal Frailty Model . . . . . . . . . . . . . . . . . 113
6.6.1 Application to Seizure Data . . . . . . . . . . . . . . .     113
6.7 Modified EM (MEM) Algorithm for Gamma Frailty Models           114
6.8 Application

然后用最基本的package "survival"

并参考你的模型可能用到的一些functions:

survreg(formula, data, weights, subset,na.action, dist="weibull",....)
  survreg.distributions include "weibull", "exponential", "gaussian",
                                "logistic","lognormal" and "loglogistic"

frailty(x, distribution="gamma", ...)
  distribution: either the gamma, gaussian or t distribution may be specified.
frailty.gamma(x, sparse = (nclass > 5), theta, df, eps = 1e-05,
              method = c("em","aic", "df", "fixed"),...)