base: Compute the baseline parameters needed for sample size...
In WR: Win Ratio Analysis of Composite Time-to-Event Outcomes

Description Usage Arguments Value References See Also Examples

Compute the baseline parameters ζ_0^2 and \boldsymbolδ_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≤ft(-≤ft[≤ft\{\exp(aξ_1)λ_Ds\right\}^κ+ ≤ft\{\exp(aξ_2)λ_Ht\right\}^κ\right]^{1/κ}\right),

where ξ_1 and ξ_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, τ_b] and followed until time τ (τ≥qτ_b), with an exponential loss-to-follow-up hazard λ_L.

1	base(lambda_D, lambda_H, kappa, tau_b, tau, lambda_L, N = 1000, seed = 12345)

`lambda_D`	Baseline hazard λ_D for death.
`lambda_H`	Baseline hazard λ_H for nonfatal event.
`kappa`	Gumbel–Hougaard copula correlation parameter κ.
`tau_b`	Length of the initial (uniform) accrual period τ_b.
`tau`	Total length of follow-up τ.
`lambda_L`	Exponential hazard rate λ_L for random loss to follow-up.
`N`	Simulated sample size for monte-carlo integration.
`seed`	Seed for monte-carlo simulation.