Description Usage Arguments Details Value Author(s) References

Fit proportional hazards model for general interval-censored data. Use MCMC method to estimate regression coefficients, baseline survival, and survival function at user-specified covariate values.

1 2 |

`L` |
a numeric vector of left timepoints of observed time intervals. |

`R` |
a numeric vector of right timepoints of observed time intervals. |

`status` |
a vector of censoring indicators: 1=left-censored, 0=right-censored. |

`xcov` |
a matrix of covariates, each column corresponds to one covariate. |

`x_user` |
a user specified vector of covariate values. |

`order` |
degree of I-splines ( |

`sig0` |
standard deviation of normal prior for each regression coefficient |

`coef_range` |
specify support domain of target density for |

`a_eta` |
shape parameter of Gamma prior for |

`b_eta` |
rate parameter of Gamma prior for |

`knots` |
a sequence of points to define I-splines. |

`grids` |
a sequence of points where baseline survival function is to be estimated. |

`niter` |
total number of iterations of MCMC chains. |

`seed` |
a user specified random seed, default is NULL. |

The baseline cumulative hazard is modeled by a linear combination of I-splines:

`sum_{l=1}^{k}(gamma_l*b_l)`

.

Function `arms`

is used to sample each regression coefficient `beta_r`

, and `coef_range`

specifies the support of the `indFunc`

in `arms`

.

a list containing the following elements:

`parbeta` |
a |

`parsurv0` |
a |

`parsurv` |
a |

`parfinv` |
a |

`grids` |
a sequence of points where baseline survival is estimated. |

Bo Cai

Lin, X., Cai, B., Wang, L., and Zhang, Z. (2015). Bayesian proportional hazards model for general interval-censored data.
*Lifetime Data Analysis*, **21** 470-490.

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