imputeYn (version 1.3)

aft.kmweight: Computing Kaplan-Meier Weights

Description

Compute Kaplan-Meier weights for weighted least squares method.

Usage

aft.kmweight(Y, delta)

Arguments

Y

survival time.

delta

status.

Value

kmwt

The Kaplan Meier weights

Details

Compute Kaplan-Meier weights that are used for weighted least squares to solve the AFT model under right censoring. This gives weights that are computed after implementation of Efron's (1967) tail correction.

References

Stute, W. (1993). Consistent estimation under random censorship when covariables are available. Journal of Multivariate Analysis, 45 , 89-103.

Efron, B. (1967). The two sample problem with censored data. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, Vol. 4, p. 831-853.

Examples

# For dataset where the last largest datum is censored and censoring level is 50 percent
data1<-data(n=100, p=2, r=0, b1=c(2,4), sig=1, Cper=0)
kmw<-aft.kmweight(data1$y,data1$delta)
kmw