DTR (version 1.1-1)

LDT.mean.estimator: Function for calculating LTD restricted mean estimator

Description

The function provides the mean restricted survival estimates and their estimated standard errors for the dynamic treatment regimes (DTRs) based on the data from sequentially randomized designs as proposed in Lunceford, Davidian and Tsiatis (2002). Because different assignments at the first stage are independent to each other, the function only calculates estimates for one of the assignments at the first stage. For example, if there are two first-stage therapies A1 and A2 available, the function only calculates estimates for one of the two arms (e.g. A1).

Usage

LDT.mean.estimator(data, L)

Arguments

data

a data frame (R, Z, V, delta) representing the data for one of the first-stage assignments from sequentially randomized designs. R: response status, R=1 for responders, and R=0 for non-responders Z: second-stage indicator, Z=0 if assigned to B1, and Z=1

L

restricted survival time. Because of the limited follow-up time, restricted lifetime is considered. We only consider survival up to some time L, where L is smaller than the maximum follow-up time

Value

• The function returns mean restricted survival estimates and their standard errors for dynamic treatment regimes A1B1 and A1B2.
• MEAN1
  LDT mean restricted survival estimates for A1B1
• MSE1
  estimated standard error for MEAN1
• MEAN2
  LDT mean restricted survival estimates for A1B2
• MSE2
  estimated standard error for MEAN2

Details

In sequentially randomized designs, there could be more than two therapies available at each stage. For simplicity, and to maintain similarity to the most common sequentially randomized clinical trials, a simple two-stage randomization design allowing two treatment options at each stage is used in the current version of the package. In detail, patients are initially randomized to either A1 or A2 at the first stage. Based on their response status, they are then randomized to either B1 or B2 at the second stage. Therefore, there are a total of four DTRs: A1B1, A1B2, A2B1, and A2B2.

References

Lunceford JK, Davidian M, Tsiatis AA: Estimation of survival distributions of treatment policies in two-stage randomization designs in clinical trials. Biometrics 58:48-57, 2002

See Also

DTR, sim.LDT.data, LDT.estimator

Examples

require(DTR)
  
#-------Example function usage-----------
n<-500
L<-1.5
max.c<-2.5
pi.r<-0.5
pi.z<-0.5
lambda<-1.33
alpha<-6.67
beta1<-0.29
beta2<--0.67

# Generate data from SRD
set.seed(123)  # Set a seed to reproduce the same data every time running the following command
data<-sim.LDT.data(n,L,max.c,pi.r,pi.z,lambda,alpha,beta1,beta2)

# Calculate LTD restricted mean estimates
LDT.mean.estimator(data, L=1.5)