LDM3df {survivalREC} | R Documentation |
Provides estimates for three gap times distribution function based on landmarking. The extension of the landmark estimator (LDM) to three gap times is a consequence of Bayes' theorem.
LDM3df(object, x, y, z)
object |
An object of class multidf. |
x |
The first time for obtaining estimates for the trivariate distribution function. |
y |
The second time for obtaining estimates for the trivariate distribution function. |
z |
The third time for obtaining estimates for the trivariate distribution function. |
Vector with the Landmark estimates for three gap times distribution function.
Gustavo Soutinho and Luis Meira-Machado
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.
data("bladder5state")
b4state<-multidf(gap1=bladder5state$y1, event1=bladder4state$d1,
gap2=bladder5state$y2, event2=bladder4state$d2,
gap3=bladder5state$y3, status=bladder4state$d3)
head(b4state)[[1]]
LDM3df(b4state, x=13, y=20, z=40)
b4<-multidf(gap1=bladder4$t1, event1=bladder4$d1,
gap2=bladder4$t2-bladder4$t1, event2=bladder4$d2,
gap3=bladder4$t3-bladder4$t2, status=bladder4state$d3)
LDM3df(b4,x=13,y=20,z=40)