simbcfraildv {bcfrailphdv} | R Documentation |

Simulate data from bivariate correlated gamma or lognormal frailty models with one covariate.

```
simbcfraildv(
psize,
cenr = c(0),
beta = c(0.5),
frailty,
frailpar = c(0.5, 0.5, 0.25),
bhaz = c("weibull"),
bhazpar = list(shape = c(0.5), scale = c(0.01)),
covartype = c("B"),
covarpar = list(fargs = c(1), sargs = c(0.5)),
inpcovar = NULL,
inpcen = NULL,
comncovar = NULL
)
```

`psize` |
pair size. |

`cenr` |
censored rate. The default is zero.. |

`beta` |
Covariate coefficient. |

`frailty` |
A type of frailty distribution to be used. Either gamma or lognormal. |

`frailpar` |
vector of frailty parameters, variance and correlation respectively. The default is c(0.5,0.5,0.25) meaning both variances are 0.5 and correlation 0.25. |

`bhaz` |
A type of baseline hazard distribution to be used. it can be weibull, gompertz or exponential. |

`bhazpar` |
is a |

`covartype` |
specified the distribution from which covariate(s) are goining to be sampled. covartype can be c("B","N","U")denoting binomial, normal or uniform, respectively. For example, |

`covarpar` |
is a |

`inpcovar` |
is a |

`inpcen` |
is a |

`comncovar` |
if common covariates are needed. |

An object of class `simbcfraildv`

that contain the following:

`data`

A data frame i.e, the simulated data set. IID is individual Id, PID is pair ID, time is the simulated survival time, censor is censoring indicator and X1 denote the simulated covariate.`numberofpair`

The specified number of pairs.`censoredrate`

The specified censored rate.`fraildist`

The specified frailty distribution.`frailpar`

The specified frailty parameters.

```
set.seed(4)
simdata<-simbcfraildv(psize=300, cenr= c(0.3),beta=c(2),frailty=c("gamma"),
frailpar=c(0.5,0.5,0.5),bhaz=c("weibull"),
bhazpar=list(shape =c(5), scale = c(0.1)),
covartype= c("B"),covarpar=list(fargs=c(1),sargs=c(0.5)))
dataa<-simdata$data
head(dataa)
# If data generation is from bivariate correlated lognormal frailty model,
set.seed(18)
simdata<-simbcfraildv(psize=100, cenr= c(0.2),beta=c(1,-0.7,0.5),frailty=c("lognormal"),
frailpar=c(0.5,0.8,-0.25),bhaz=c("exponential"),
bhazpar=list(scale = c(0.1)),covartype= c("N","N","B"),
covarpar=list(fargs=c(0,0,1),sargs=c(1,1,0.5)))
dataa<-simdata$data
head(dataa)
# If common covariate is desired, i.e., here out of the three covariates
#covariate 2 is common for the pair.
set.seed(18)
simdata<-simbcfraildv(psize=100, cenr= c(0.2),beta=c(1,-0.7,0.5),frailty=c("lognormal"),
frailpar=c(0.5,0.8,-0.25),bhaz=c("exponential"),
bhazpar=list(scale = c(0.1)),covartype= c("N","N","B"),
covarpar=list(fargs=c(0,0,1),sargs=c(1,1,0.5)),comncovar=2)
dataa<-simdata$data
head(dataa)
# If the data generation is from bivariate correlated gamma frailty model,
#weibull baseline and without covariate,
set.seed(4)
simdata<-simbcfraildv(psize=300, cenr= c(0.3),beta=NULL,frailty=c("gamma"),
frailpar=c(0.5,0.6,0.5),bhaz=c("weibull"),bhazpar=list(shape =c(5), scale = c(0.1)))
dataa<-simdata$data
head(dataa)
```

[Package *bcfrailphdv* version 0.1.1 Index]