MTAFT_IC {MTAFT}

MTAFT_IC: Multiple Thresholds Accelerated Failure Time Model with Information Criteria

Description

This function implements a method for multiple thresholds accelerated failure time (AFT) model with information criteria. It estimates the subgroup-specific slope coefficients and variance estimates, as well as the threshold estimates using either the "WBS" (Wild Binary Segmentation) or "DP" (Dynamic Programming) algorithm.

Usage

MTAFT_IC(
  Y,
  X,
  delta,
  Tq,
  c0 = 0.299,
  delta0 = 2.01,
  algorithm = c("WBS", "DP"),
  dist_min = 50,
  ncps_max = 4,
  wbs_nintervals = 200
)

Arguments

Y

the censored logarithm of the failure time.

X

the design matrix without the intercept.

delta

the censoring indicator.

Tq

the threshold values.

c0

the penalty factor c0 in the information criteria (IC), default is 0.299.

delta0

the penalty factor delta0 in the information criteria (IC), default is 2.01.

algorithm

the threshold detection algorithm, either "WBS" or "DP". Default is "WBS".

dist_min

the pre-specified minimal number of observations within each subgroup. Default is 50.

ncps_max

the pre-specified maximum number of thresholds. Default is 4.

wbs_nintervals

the number of random intervals in the WBS algorithm. Default is 200.

Value

A list with the following components:

params

the subgroup-specific slope estimates and variance estimates.

thres

the threshold estimates.

IC_val

the IC values for all candidate number of thresholds.

References

(Add relevant references here)

Examples

# Generate simulated data with 500 samples and normal error distribution
dataset <- MTAFT_simdata(n = 500, err = "normal")
Y <- dataset[, 1]
delta <- dataset[, 2]
Tq <- dataset[, 3]
X <- dataset[, -c(1:3)]

# Run MTAFT_IC with WBS algorithm
mtaft_ic_result <- MTAFT_IC(Y, X, delta, Tq, algorithm = 'WBS')
mtaft_ic_result$params
mtaft_ic_result$thres
mtaft_ic_result$IC_val