rankaft {rankreg}R Documentation

Compute Rank estimator in censored AFT model

Description

Compute the Gehan and Logrank type rank regression estimators in the censored AFT model. Using linear programming.

Usage

rankaft(x, y, delta)  

Arguments

x the design matrix, of size n by q.
y a vector containing the censored responses in the AFT model.
delta a vector of 1's and 0's. censoring indicator. 1(uncensor), 0(censored). Both y and delta should be of length n.

Details

This program is memory hungary. Caution needed for sample size over 1000.

To further save computing time/memory, we cut the re-sampling part. Instead, the inference can be obtained by empirical likelihood.

Value

A list with beta which is the Gehan and Logrank type estimate rbind together; and residuals.

Author(s)

Original Splus code by Jin Z. Adapted to R by Mai Zhou.

References

Kalbfleisch, J. and Prentice, R. (2002) {em The Statistical Analysis of Failure Time Data}. 2nd Ed. Wiley, New York. (Chapter 7)

Jin, Z., Lin, D.Y., Wei, L. J. and Ying, Z. (2003). Rank-based inference for the accelerated failure time model. {em Biometrika}, {bf 90}, 341-353.

Examples

data(myeloma)
rankaft(x=cbind(myeloma[,3],myeloma[,4]),y=myeloma[,1],delta=myeloma[,2])

[Package rankreg version 0.2 Index]