# frailty: Example of a simulation study on frailty survival models In rsimsum: Analysis of Simulation Studies Including Monte Carlo Error

 frailty R Documentation

## Example of a simulation study on frailty survival models

### Description

A dataset from a simulation study comparing frailty flexible parametric models fitted using penalised likelihood to semiparametric frailty models. Both models are fitted assuming a Gamma and a log-Normal frailty. One thousand datasets were simulated, each containing a binary treatment variable with a log-hazard ratio of -0.50. Clustered survival data was simulated assuming 50 clusters of 50 individuals each, with a mixture Weibull baseline hazard function and a frailty following either a Gamma or a Log-Normal distribution. The comparison involves estimates of the log-treatment effect, and estimates of heterogeneity (i.e. the estimated frailty variance).

### Usage

```frailty

frailty2
```

### Format

A data frame with 16,000 rows and 6 variables:

• `i` Simulated dataset number.

• `b` Point estimate.

• `se` Standard error of the point estimate.

• `par` The estimand. `trt` is the log-treatment effect, `fv` is the variance of the frailty.

• `fv_dist` The true frailty distribution.

• `model` Method used (`Cox, Gamma`, `Cox, Log-Normal`, `RP(P), Gamma`, or `RP(P), Log-Normal`).

An object of class `data.frame` with 16000 rows and 7 columns.

### Note

`frailty2` is a version of the same dataset with the `model` column split into two columns, `m_baseline` and `m_frailty`.

### Examples

```data("frailty", package = "rsimsum")
data("frailty2", package = "rsimsum")
```

rsimsum documentation built on Aug. 17, 2022, 5:07 p.m.