TTOT_fun: Compute the Total Time-on-Test (TTOT) Statistic

In DTEBOP2: Bayesian Optimal Phase II Randomized Clinical Trial Design with Delayed Outcomes

Compute the Total Time-on-Test (TTOT) Statistic

Description

Calculates the Total Time-on-Test (TTOT) statistic for a given vector of event times and censoring indicators. The TTOT function is commonly used in survival analysis for visualizing and assessing the cumulative hazard or comparing survival patterns between groups.

Usage

TTOT_fun(data, tA = 0, tB = 10000, t)

Arguments

data	A data frame containing the input survival data. The first column should be named "Time" and contain the observed survival times (e.g., in months or years). The second column should be named "Status", where 0 indicates a censored observation and 1 indicates an event.
tA	Numeric. The starting time point for computing the Total Time-on-Test (TTOT) function.
tB	Numeric. The ending time point for computing the TTOT function.
t	Numeric. The time point(s) at which the TTOT function is evaluated.

Value

This function calculates the total time-on-test (TTOT) for a given dataset within the time interval (tA,tB).

Examples

# Generate sample survival data
set.seed(123)
sim_time <- generate_pe(n = 20, t = 1, lambda1 = 1, lambda2 = 0.5)
sim_status <- sample(c(0, 1), 20, replace = TRUE)
Data <- data.frame(Time = sim_time, Status = sim_status)
# Compute TTOT when time = 1
TTOT_fun(Data, t = 1)

DTEBOP2 documentation built on June 8, 2025, 1:24 p.m.