summary.bayesmixsurv {BayesMixSurv}

Summarizing BayesMixSurv model fits

Description

summary method for class "bayesmixsurv".

Usage

## S3 method for class 'bayesmixsurv'
summary(object, pval = 0.05, burnin = object$control$burnin, ...)
## S3 method for class 'summary.bayesmixsurv'
print(x, ...)

Arguments

object

An object of class 'bayesmixsurv', usually the result of a call to bayesmixsurv.

x

An object of class "summary.bayesmixsurv", usually the result of a call to summary.bayesmixsurv.

pval

Desired p-value, based on which lower/upper bounds will be calculated. Default is 0.05.

burnin

Number of samples to discard from the beginning of each MCMC chain before calculating median and lower/upper bounds.

...

Further arguments to be passed to/from other methods.

Value

An object of class summary.bayesmixsurv, with the following elements:

call

The matched call.

pval

Same as input.

burnin

Same as input.

single

Copied from object$control$single. See bayesmixsurv.control for explanation.

coefficients

A list including matrices alpha, beta1, beta2, and gamma (if stratification is used). Each matrix has columns named 'Estimate', 'Lower Bound', 'Upper Bound', and 'P-val'. alpha has two rows, one for each components, while each of beta1 and beta2 has one row per covariate. gamma has one row per stratum (except for the reference stratum).

Author(s)

Alireza S. Mahani, Mansour T.A. Sharabiani

See Also

See summary for a description of the generic method.

The model fitting function is bayesmixsurv.

Examples

est <- bayesmixsurv(Surv(futime, fustat) ~ ecog.ps + rx, ovarian
            , control=bayesmixsurv.control(iter=800, nskip=100))
summary(est, pval=0.1)