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.
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