Description Usage Arguments Details Value Author(s) References

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

1 2 | ```
case2probit(L, R, status, xcov, x_user, order, m0,
v0, a_eta, b_eta, knots, grids, niter, seed)
``` |

`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: 0=left-censored, 1=interval-censored, 2=right-censored. |

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

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

`order` |
degree of I-splines ( |

`m0` |
mean of normal prior for |

`v0` |
precision of normal prior 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. Default is minimum observed time points. |

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

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

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

`gamma_0+sum_{l=1}^{k}(gamma_l*b_l)`

.

Regression coefficient vector `beta`

is sampled from a multivariate normal distribution.
For more information, please see reference.

a list containing the following elements:

`parbeta` |
a |

`parsurv0` |
a |

`parsurv` |
a |

`parfinv` |
a |

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

Lianming Wang and Xiaoyan Lin. R version by Bo Cai.

Lin, X. and Wang, L. (2009). A semiparametric probit model for case 2 interval-censored failure time data.
*Statistics in Medicine* **29** 972-981.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.