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ICBayes (version 1.2)

case2ph: PH model for general interval-censored data

Description

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.

Usage

case2ph(L, R, status, xcov, x_user, order, sig0, coef_range, 
	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: 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 (b_l) (see details). Recommended values are 2-4.

sig0

standard deviation of normal prior for each regression coefficient beta_r.

coef_range

specify support domain of target density for beta_r sampled by arms (see details).

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.

niter

total number of iterations of MCMC chains.

seed

a user specified random seed, default is NULL.

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.

Details

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.

References

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.