survivalREC (version 1.1)

LDMdf: Landmark estimator for the bivariate distribution function

Description

Provides estimates for the bivariate distribution function based on Bayes' theorem and Kaplan-Meier survival function. This approach is also named as landmarking.

Usage

LDMdf(object, x, y)

Value

Vector with the Landmark estimates for the bivariate distribution function.

Arguments

object

An object of class multidf.

x

The first time for obtaining estimates for the bivariate distribution function.

y

The second time for obtaining estimates for the bivariate distribution function.

Author

Gustavo Soutinho and Luis Meira-Machado

References

van Houwelingen, H.C. (2007). Dynamic prediction by landmarking in event history analysis, Scandinavian Journal of Statistics, 34, 70-85.

Kaplan, E. and Meier, P. (1958). Nonparametric Estimation from Incomplete Observations, Journal of the American Statistical Association 53(282), 457-481.

See Also

IPCWdf, KMWdf, LINdf and WCHdf.

Examples

b3state<-multidf(gap1=bladder4state$y1, event1=bladder4state$d1, 
                 gap2=bladder4state$y2, status=bladder4state$d2, 
                 size=bladder4state$size)
                 
LDMdf(b3state, x=13, y=20)