Description Usage Arguments Details Value Author(s) References See Also Examples

Calls the `case1ph`

, `case2ph`

, or `case2probit`

function to fit the corresponding model.
Give point estimates and credible intervals for regression coefficients and estimation and plot of survival functions.

1 2 3 4 5 6 7 8 9 |

`L` |
a column vector of left-points of observed time intervals. |

`R` |
a column vector of right-points of observed time intervals. Use NA to denote infinity. |

`model` |
a character string specifying the type of model. Possible values are "case1ph", "case2ph", "case2po", and "case2probit". |

`status` |
a vector of censoring indicators. If |

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

`x_user` |
a vector of covariate values, default is NULL. Need to specify for survival estimation. |

`order` |
degree of I-splines ( |

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

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

`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. Default is a sequence of time points from min to max with length=10. |

`grids` |
a sequence of points where survival function is to be estimated. Defalult is a sequence of time points from min to max with length=100. |

`conf.int` |
level for a two-sided credible interval on coefficient estimate(s). Default is 0.95. |

`niter` |
total number of iterations of MCMC chains. Default is 5000. |

`burnin` |
number of iterations to discard at the beginning of an MCMC run. Default is 1000. |

`thin` |
specify thinning of MCMC draws. Default is 1. |

`seed` |
a use-specified random seed. Default is NULL. |

`formula` |
a symbolic description of the model to be fit. |

`data` |
a data frame containing the variables in the model. |

`...` |
values passed to other functions. |

For "case1ph", "case1po", and "case2ph" models, function `arms`

is used to sample regression coefficient `beta_r`

, and `coef_range`

specifies the support of the `indFunc`

in `arms`

. The baseline cumulative hazard in "case1ph"and "case2ph" models and the baseline odds function in "case1po" are modeled by a linear combination of I-splines:

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

.

For "case2probit" model, baseline function is modeled by a linear combination of I-splines:

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

.

For "case2probit" model, regression coefficient vector `beta`

is sampled from a multivariate normal distribution.

For more information, please see reference.

an object of class `ICBayes`

containing the following elements:

`coef` |
a vector of regression coefficient estimates |

`coef_ssd` |
a vector of sample standard deviations of regression coefficient estimates |

`coef_ci` |
credible intervals for regression coefficients |

`LPML` |
log pseudo marginal likelihood for model selection, the larger the better |

`grids` |
the sequance of points where baseline survival functions is estimated |

`h0_m` |
estimated baseline hazard at |

`h_m` |
a |

`h_ci` |
credible intervals for hazard function at |

`S0_m` |
estimated baseline survival probabilities at |

`S_m` |
a |

`S_ci` |
credible intervals for survival probablities at |

`mcmc_beta` |
a |

`mcmc_surv` |
a |

Chun Pan

Cai, B., Lin, X., and Wang, L. (2011). Bayesian proportional hazards model for current status data with monotone splines.
*Computational Statistics and Data Analysis*, **55** 2644-2651.

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

Lin, X. and Wang, L. (2011). Bayesian proportional odds model for analyzing current status data: univariate, clustered, and multivariate.
*Communication in Statistics-Simulation and Computation*, **40** 1171-1181.

Lin, X., Cai, B., Wang, L., and Zhang, Z. (submitted). Bayesian proportional hazards model for general interval-censored data.

`case1ph`

, `case1po`

, `case2ph`

, `case2probit`

1 2 3 4 5 6 7 8 9 10 11 | ```
# To save time in checking package, niter is set to only 500 iterations.
# formula form
data(bcdata)
bcdata<-data.frame(bcdata) # must be a data frame
try<-ICBayes(Surv(L,R,type='interval2')~x1,data=bcdata,
model='case2ph',status=bcdata[,3],x_user=c(0,1),knots=seq(0.1,60.1,length=10),
grids=seq(0.1,60.1,by=1),coef.int=0.95,niter=500,burnin=100,seed=20161224)
# general form
try2<-ICBayes(model='case2ph',L=bcdata[,1],R=bcdata[,2],status=bcdata[,3],
xcov=bcdata[,4],x_user=c(0,1),knots=seq(0.1,60.1,length=10),
grids=seq(0.1,60.1,by=1),coef.int=0.95,niter=500,burnin=100,seed=20161224)
``` |

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