| base {WR} | R Documentation |
Compute the baseline parameters needed for sample size calculation for standard win ratio test
Description
Compute the baseline parameters \zeta_0^2 and \boldsymbol\delta_0
needed for sample size calculation for standard win ratio test (see WRSS).
The calculation is based
on a Gumbel–Hougaard copula model for survival time D^{(a)} and nonfatal event
time T^{(a)} for group a (1: treatment; 0: control):
{P}(D^{(a)}>s, T^{(a)}>t) =\exp\left(-\left[\left\{\exp(a\xi_1)\lambda_Ds\right\}^\kappa+
\left\{\exp(a\xi_2)\lambda_Ht\right\}^\kappa\right]^{1/\kappa}\right),
where \xi_1 and \xi_2 are the component-wise log-hazard ratios to be used
as effect size in WRSS.
We also assume that patients are recruited uniformly over the period [0, \tau_b]
and followed until time \tau (\tau\geq\tau_b), with an exponential
loss-to-follow-up hazard \lambda_L.
Usage
base(lambda_D, lambda_H, kappa, tau_b, tau, lambda_L, N = 1000, seed = 12345)
Arguments
lambda_D |
Baseline hazard |
lambda_H |
Baseline hazard |
kappa |
Gumbel–Hougaard copula correlation parameter |
tau_b |
Length of the initial (uniform) accrual period |
tau |
Total length of follow-up |
lambda_L |
Exponential hazard rate |
N |
Simulated sample size for monte-carlo integration. |
seed |
Seed for monte-carlo simulation. |
Value
A list containing real number zeta2 for \zeta_0^2
and bivariate vector delta for \boldsymbol\delta_0.
References
Mao, L., Kim, K. and Miao, X. (2021). Sample size formula for general win ratio analysis. Biometrics, https://doi.org/10.1111/biom.13501.
See Also
Examples
# see the example for WRSS