This function calculates the probability that an individual has the event of interest before t0 + tau given the event has not yet occurred and the individual is still at risk at time t0; this estimated probability does not incorporate any information about the covariate or short term event information.
the residual survival time for which probabilities are calculated. Specifically, this function estimates the probability that the an individual has the event of interest before t0 + tau given the event has not yet occurred and the individual is still at risk at time t0.
data
n by k matrix, where k >=2. A data matrix where the first column is XL = min(TL, C) where TL is the time of the long term event, C is the censoring time, and the second column is DL =1*(TL<C). These are the data used to calculate the estimated probability.
weight
an optional weight to be incorporated in all estimation.
newdata
an optional n by k matrix, where k >=2. A data matrix where the first column is XL = min(TL, C) where TL is the time of the long term event, C is the censoring time, and the second column is DL =1*(TL<C). Predicted probabilities are estimated for these data.
Value
Prob
Estimated probability that the an individual has the event of interest before t0 + tau given the event has not yet occurred and the individual is still at risk at time t0; this estimated probability does not incorporate any information about the covariate or short term event information.
data
the data matrix with an additional column with the estimated individual probabilities; note that the predicted probability is NA if TL <t0 since it is only defined for individuals with TL> t0
newdata
the newdata matrix with an additional column with the estimated individual probabilities; note that the predicted probability is NA if TL <t0 since it is only defined for individuals with TL> t0; if newdata is not supplied then this returns NULL
Author(s)
Layla Parast
References
Parast, Layla, Su-Chun Cheng, and Tianxi Cai. Incorporating short-term outcome information to predict long-term survival with discrete markers. Biometrical Journal 53.2 (2011): 294-307.
Examples
data(data_example_landpred)
t0=2
tau = 8
Prob.Null(t0=t0,tau=tau,data=data_example_landpred)
out = Prob.Null(t0=t0,tau=tau,data=data_example_landpred)
out$Prob
out$data
newdata = matrix(c(1,1,3,0,4,1,10,1,11,0), ncol = 2, byrow=TRUE)
out = Prob.Null(t0=t0,tau=tau,data=data_example_landpred,newdata=newdata)
out$Prob
out$newdata
providing 
.