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WR (version 1.0)

base: 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 \(\lambda_D\) for death.

lambda_H

Baseline hazard \(\lambda_H\) for nonfatal event.

kappa

Gumbel--Hougaard copula correlation parameter \(\kappa\).

tau_b

Length of the initial (uniform) accrual period \(\tau_b\).

tau

Total length of follow-up \(\tau\).

lambda_L

Exponential hazard rate \(\lambda_L\) for random loss to follow-up.

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

gumbel.est, WRSS

Examples

Run this code
# NOT RUN {
# see the example for WRSS
# }

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