dtl_app_sim {dtlcor}R Documentation

Simulation study for drop-the-losers (DTL) trial.

Description

Simulation study for a trial based on the DTL design

Usage

dtl_app_sim(
  nsim,
  alpha_t,
  D,
  N,
  n,
  mPFS,
  q,
  gamma,
  drop_rate,
  enroll,
  interim_t,
  sel_g_func = sel_g_func_default,
  ...
)

Arguments

nsim

Number of replicates.

alpha_t

significance level for the final stage (recommend to use minimum significance level alpha_t to control family-wise type I error rate).

D

Total number of events.

N

Total number of patients in both selected and control arms at final analysis.

n

Number of patients per treatment arm at the DTL look.

mPFS

A 3-entry vector of median progression-free survival times (in days) for control, low dose and high dose arms.

q

A 3-entry vector of response rates under the null.

gamma

Hazards ratio of responders and non-responders.

drop_rate

Annual drop-out rate.

enroll

Annual enrollment rate.

interim_t

A vector of information fractions of final stage.

sel_g_func

Arm-select function. The default function is sel_g_func_default(W_2, W_1, delta). Users can define their own arm-select function. The format of the function must be function_name(W_2, W_1, ...). The return values must be 1 (arm 1 is selected) or 2 (arm 2 is selected) or 0 (stop for futility).

...

Other arguments from sel_g_func.

Value

A one row data frame of simulation results, including the parameter settings, the O'Brien-Fleming boundaries for interim and final analyses: c.1, c.2, the overall censoring rate: cen_rate, the mean study duration: dur, the probability of selecting high dose / low dose / no dose: prob_sel_2, prob_sel_1, prob_sel_0, the probability of rejecting H_1 or H_2: rej_12, the probability of rejecting H_1 only: rej_1, the probability of rejecting H_2 only: rej_2.

Examples


# Inputs
set.seed(1000)
nsim        = 1000
alpha_t     = 0.018
D           = 162
N           = 152  
n           = 80    
mPFS        = c(180, 276, 300)
q           = c(0.2, 0.4, 0.5)
mPFS_null   = rep(180, 3)
q_null      = rep(0.2, 3)
gamma       = 0.15
drop_rate   = 0.05
enroll      = 20 * 12
interim_t   = c(0.5, 1)
delta       = 0.05  

# Type I Error
dtl_app_sim(nsim, alpha_t, D, N, n, mPFS_null, q_null, gamma, drop_rate, 
            enroll, interim_t, delta = delta)

# Power
dtl_app_sim(nsim, alpha_t, D, N, n, mPFS, q, gamma, drop_rate, enroll, 
            interim_t, delta = delta)



[Package dtlcor version 0.1.0 Index]