PICBayes {PICBayes} | R Documentation |
Bayesian models for partly interval-censored data and general interval-censored data
Description
Calls one of the 16 functions to fit the correspoinding model.
Usage
PICBayes(L, ...)
## Default S3 method:
PICBayes(L,R,y,xcov,IC,model,scale.designX,scaled,xtrt,zcov,
area,binary,I,C,nn,order=3,knots,grids,a_eta=1,b_eta=1,a_ga=1,b_ga=1,a_lamb=1,
b_lamb=1,a_tau=1,b_tau=1,a_tau_trt=1,b_tau_trt=1,a_alpha=1,b_alpha=1,H=5,
a_tau_star=1,b_tau_star=1,a_alpha_trt=1,b_alpha_trt=1,H_trt=5,
a_tau_trt_star=1,b_tau_trt_star=1,beta_iter=1001,phi_iter=1001,
beta_cand,phi_cand,beta_sig0=10,x_user=NULL,
total=6000,burnin=1000,thin=1,conf.int=0.95,seed=1,...)
## S3 method for class 'formula'
PICBayes(formula, data, ...)
Arguments
L |
The vector of left endpoints of the observed time intervals. |
R |
The vector of right endponts of the observed time intervals. |
y |
The vector of censoring indicator: 0=left-censored, 1=interval-censored, 2=right-censored, 3=exact. |
xcov |
The covariate matrix for the p predictors. |
IC |
The vector of general interval-censored indicator: 1=general interval-censored, 0=exact. |
model |
A character string specifying the type of model. See details. |
scale.designX |
The TRUE or FALSE indicator of whether or not to scale the design matrix X. |
scaled |
The vector indicating whether each covariate is to be scaled: 1=to be scaled, 0=not. |
xtrt |
The covariate that has a random effect. |
zcov |
The design matrix for the q random effects. |
area |
The vector of cluster ID. |
I |
The number of areas. |
C |
The adjacency matrix. |
nn |
The vector of number of neighbors for each area. |
binary |
The vector indicating whether each covariate is binary. |
order |
The degree of basis I-splines: 1=linear, 2=quadratic, 3=cubic, etc. |
knots |
A sequence of knots to define the basis I-splines. |
grids |
A sequence of points at which baseline survival function is to be estimated. |
a_eta |
The shape parameter of Gamma prior for |
b_eta |
The rate parameter of Gamma prior for |
a_ga |
The shape parameter of Gamma prior for |
b_ga |
The rate parameter of Gamma prior for |
a_lamb |
The shape parameter of Gamma prior for spatial precision |
b_lamb |
The rate parameter of Gamma prior for spatial precision |
a_tau |
The shape parameter of Gamma prior for random intercept precision |
b_tau |
The rate parameter of Gamma prior for random intercept precision |
a_tau_trt |
The shape parameter of Gamma prior for random treatment precision |
b_tau_trt |
The rate parameter of Gamma prior for random treatment precision |
a_alpha |
The shape parameter of Gamma prior for |
b_alpha |
The rate parameter of Gamma prior for |
H |
The number of distinct components in DP mixture prior under blocked Gibbs sampler. |
a_tau_star |
The shape parameter of |
b_tau_star |
The rate parameter of |
a_alpha_trt |
The shape parameter of Gamma prior for |
b_alpha_trt |
The rate parameter of Gamma prior for |
H_trt |
The number of distinct components in DP mixture prior under blocked Gibbs sampler for random treatment. |
a_tau_trt_star |
The shape parameter of |
b_tau_trt_star |
The rate parameter of |
beta_iter |
The number of initial iterations in the Metropolis-Hastings sampling for |
phi_iter |
The number of initial iterations in the Metropolis-Hastings sampling for |
beta_cand |
The sd of the proposal normal distribution in the MH sampling for |
phi_cand |
The sd of the proposal normal distribution in the initial MH sampling for |
beta_sig0 |
The sd of the prior normal distribution for |
x_user |
The user-specified covariate vector at which to estimate survival function(s). |
total |
The number of total iterations. |
burnin |
The number of burnin. |
thin |
The frequency of thinning. |
conf.int |
The confidence level of the CI for |
seed |
A user-specified random seed. |
formula |
A formula expression with the response returned by the Surv function in the survival package. |
data |
A data frame that contains the variables named in the formula argument. |
... |
Other arguments if any. |
Details
Possible values are "PIC", "spatialPIC", "clusterPIC_int", "clusterPIC_int_DP", "clusterPIC_trt", "clusterPIC_trt_DP", "clusterPIC_Z", and "clusterPIC_Z_DP" for partly interval-censored data; and "IC", "spatialIC", "clusterIC_int", "clusterIC_int_DP", "clusterIC_trt", "clusterIC_trt_DP", "clusterIC_Z", and "clusterIC_Z_DP" for general interval-censored data.
Value
An object of class PICBayes
. Refere to each specific function for its specific values.
Author(s)
Chun Pan