case1ph: PH model for case 1 interval-censored data
In ICBayes: Bayesian Semiparametric Models for Interval-Censored Data

Description Usage Arguments Details Value Author(s) References

Fit proportional hazards model for case 1 interval-censored data. Use MCMC method to estimate regression coefficients, baseline survival, and survival at user-specified covariate values.

1 2	case1ph(L, R, status, xcov, x_user, order, sig0, coef_range, 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: 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.

The baseline cumulative hazard is approximated 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 `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.

Bo Cai

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.

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