case2probit: Probit model for general interval-censored data

In ICBayes: Bayesian Semiparametric Models for Interval-Censored Data

Description

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.

Usage

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

Arguments

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 (b_l) (see details). Recommended values are 2-4.
m0	mean of normal prior for gamma_0.
v0	precision of normal prior for gamma_0.
a_eta	shape parameter of Gamma prior for gamma_l (see details).
b_eta	rate parameter of Gamma prior for gamma_l (see details).
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.

Details

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.

Value

a list containing the following elements:

parbeta	a niter by p matrix of MCMC draws of beta_r, r=1, ..., p.
parsurv0	a niter by length(grids) matrix, each row contains the baseline survival at grids from one iteration.
parsurv	a niter by length(grids)*G matrix, each row contains the survival at grids from one iteration. G is the number of sets of user-specified covariate values.
parfinv	a niter by n matrix, each row contains the inverse PDF of observed interval-censored data from one iteration. This is used for computing LPML later.
grids	a sequence of points where baseline survival is estimated.

Author(s)

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

References

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

ICBayes documentation built on Feb. 1, 2020, 1:07 a.m.