cif2.int {surv2sample}R Documentation

Two-Sample Integrated-Difference Test for Cumulative Incidence Functions

Description

Compares cumulative incidence functions (CIF) for one failure cause in two samples of censored competing risks data using the test based on the integrated difference of CIFs.

Usage

cif2.int(x, group, cause = 1, tau, nsim = 0)

Arguments

x a "Survcomp" object, as returned by the Survcomp function.
group a vector indicating to which group each observation belongs. May contain values 1 and 2 only.
cause For which cause of failure should the CIFs be compared?
tau the upper limit of the integral in the test statistic. If missing, defaults to the maximum of times.
nsim the number of simulations used to approximate the distribution of the test statistic. If 0, no simulations are carried out and the asymptotic normal approximation is used.

Details

The test compares cumulative incidence functions F_1(t,k), F_2(t,k) for a particular failure cause k.

The method is based on the statistic proposed by Pepe (1991) which is the integral of F_2(t,k)-F_1(t,k) from 0 to tau. The martingale-based simulation technique and the variance estimator are described in Bajorunaite and Klein (2007).

Value

A list of class "cif2.int" with components:

stat the test statistic.
pval.asympt the p-value based on the asymptotic normality.
pval.sim the p-value based on simulations (if nsim>0).

Further components are cause, tau, nsim, the same as on input.

Author(s)

David Kraus (http://www.davidkraus.net/)

References

Bajorunaite, R. and Klein, J. P. (2007) Two-sample tests of the equality of two cumulative incidence functions. Comput. Statist. Data Anal. 51, 4269–4281.

Pepe, M. S. (1991) Inference for events with dependent risks in multiple endpoint studies. J. Amer. Statist. Assoc. 86, 770–778.

See Also

cif and plot.cif for estimation and plotting of CIFs

cif2.ks, cif2.logrank and cif2.neyman for other two-sample tests

Examples

## bone marrow transplant data
data(bmt1)

## compare CIFs for cause 1 (relapse)
cif2.int(Survcomp(bmt1$time, bmt1$event), bmt1$donor, cause = 1)

## compare CIFs for cause 2 (death in remission)
cif2.int(Survcomp(bmt1$time, bmt1$event), bmt1$donor, cause = 2)

[Package surv2sample version 0.1-2 Index]