Fast Regression for the Accelerated Failure Time (AFT) Model

Package fastAFT performs fast censored linear regression for the accelerated failure time (AFT) model of Huang (2013).

Installation

fastAFT is available on CRAN:

install.packages("fastAFT")

Fast censored linear regression

This procedure is illustrated with the Mayo primary biliary cholangitis dataset as given in package survival.

## Mayo PBC data
library(survival)
pbc_analy <- as.matrix(na.omit(pbc[,c("time","status","age","edema","bili","albumin","protime")]))
# log transformation for time, bili, albumin, and protime
pbc_analy[,c(1,5:7)] <- log(pbc_analy[,c(1,5:7)])
colnames(pbc_analy)[c(1,5:7)] <- paste("log",colnames(pbc_analy)[c(1,5:7)])
# convert status to censoring indicator
pbc_analy[,2] <- pbc_analy[,2]>1

## Fast censored linear regression
# Gehan weight
library(fastAFT)
fit.g <- faft(pbc_analy[,1],pbc_analy[,2],pbc_analy[,-c(1,2)],weight="Gehan")
fit.g
#> $weight
#> [1] "Gehan"
#> 
#> $beta
#> [1] -0.02549952 -0.92412231 -0.55811512  1.49837857 -2.77646687
#> 
#> $va
#>               [,1]          [,2]          [,3]         [,4]         [,5]
#> [1,]  0.0000366406 -0.0003577235  0.0001358624 0.0004583965 -0.001044045
#> [2,] -0.0003577235  0.0455455105 -0.0010112747 0.0249373432 -0.036766480
#> [3,]  0.0001358624 -0.0010112747  0.0045359974 0.0072801994 -0.022131922
#> [4,]  0.0004583965  0.0249373432  0.0072801994 0.2643719225  0.074493701
#> [5,] -0.0010440445 -0.0367664801 -0.0221319222 0.0744937012  0.604187156
#> 
#> $qif
#> [1] 1.652073e-06
#> 
#> $message
#> [1] "success"
#> 
#> $imsg
#> [1] 0
#> 
#> $beta1stp
#> [1] -0.02513122 -0.91952836 -0.55245514  1.49800515 -2.73113455
#> 
#> $qif1stp
#> [1] 0.02322713
#> 
#> $betainit
#> [1] -0.02499105 -0.83864113 -0.55202403  1.46409001 -2.11973992
#> 
#> $qifinit
#> [1] 1.790893
# logrank weight
fit.l <- faft(pbc_analy[,1],pbc_analy[,2],pbc_analy[,-c(1,2)],weight="logrank")
fit.l
#> $weight
#> [1] "logrank"
#> 
#> $beta
#> [1] -0.02578363 -0.71082797 -0.57494006  1.63506302 -1.84854122
#> 
#> $va
#>               [,1]          [,2]          [,3]         [,4]          [,5]
#> [1,]  2.657226e-05 -0.0001535839  4.308784e-05 0.0003384092 -5.294887e-05
#> [2,] -1.535839e-04  0.0543384863 -3.602356e-04 0.0433629858 -2.580506e-02
#> [3,]  4.308784e-05 -0.0003602356  3.358849e-03 0.0042775322 -9.645149e-03
#> [4,]  3.384092e-04  0.0433629858  4.277532e-03 0.2672978288  4.598259e-02
#> [5,] -5.294887e-05 -0.0258050586 -9.645149e-03 0.0459825945  4.787629e-01
#> 
#> $qif
#> [1] 3.209577e-06
#> 
#> $message
#> [1] "success"
#> 
#> $imsg
#> [1] 0
#> 
#> $beta1stp
#> [1] -0.02601255 -0.74051774 -0.57580009  1.60894096 -1.81817896
#> 
#> $qif1stp
#> [1] 0.00877687
#> 
#> $betainit
#> [1] -0.02499105 -0.83864113 -0.55202403  1.46409001 -2.11973992
#> 
#> $qifinit
#> [1] 0.5322754

References

Huang, Y. (2013) Fast censored linear regression. Scandinavian Journal of Statistics 40, 789–806.