adjusted_CIF: Calculate the adjusted CIF probability

In Lesly1031/AdjKM.CIF: A package for generating covariate-adjusted Kaplan-Meier and cumulative incidence functions

Calculate the adjusted CIF probability

Description

Use input data, time, status, grouping variables, adjusted covariates, events of interests, whether to use stratified model, and reference group as inputs

Usage

adjusted_CIF(
  data,
  time,
  status,
  group,
  covlist,
  event_code = 1,
  stratified = "Yes",
  reference_group = "G&B"
)

Arguments

data	the input dataset
time	column name of time variable
status	column name of event status
group	grouping variable
covlist	list of covariates that should be included in the model
event_code	event of interests
stratified	"Yes" refers to use stratified model, "No" refers to use Fine and Gray regression
reference_group	NULL- unstratified FG when stratified = No; "G&B"- G&B when stratified = Yes; Otherwise, Storer's approach will be performed when using a self-defined reference

Value

Output is a dataframe with adjusted CIF probabilities. If the PH assumption is invalid or if practitioners need a method by which the event time points of the adjusted function match those of the unadjusted function, the stratified model should be used (Gail and Byar and Storer et. al), otherwise, unstratified FG model can be used.

Examples

library(KMsurv)
data(bmt)
bmt$arm <- bmt$group
bmt$arm = factor(as.character(bmt$arm), levels = c("2", "1", "3"))
bmt$z3 = as.character(bmt$z3)

bmt$CenCI <- 0
for (ii in 1:137) {
  if (bmt$d3[ii] == 0) {
    bmt$CenCI[ii] <- 0
  } else {
    if (bmt$d2[ii] == 1) {
      bmt$CenCI[ii] <- 1
    } else {
      bmt$CenCI[ii] <- 2
    }
  }
}

bmt$t2 = bmt$t2 * 12/365.25

# unstratified FG
result1 = adjusted_CIF(data = bmt, time = "t2", status = "CenCI", group = "arm",
covlist = c("z1", "z3"), event_code = 1, stratified = "No", reference_group = NULL)
# stratified G&B
result2 = adjusted_CIF(data = bmt, time = "t2", status = "CenCI", group = "arm",
covlist = c("z1", "z3"), event_code = 1, stratified = "Yes", reference_group = "G&B")
# stratified Storer
result3 = adjusted_CIF(data = bmt, time = "t2", status = "CenCI", group = "arm",
covlist = c("z1", "z3"), event_code = 1, stratified = "Yes", reference_group = "arm:2")

Lesly1031/AdjKM.CIF documentation built on March 10, 2023, 12:02 p.m.