GPW.logrank {DelayedEffect.Design}

Generalized Piecewise Weighted Logrank Test

Description

Compute the p-value based on the generalized piecewise weighted log-rank test when the treatment time-lag effect is present and the lag duration varies heterogeneously from individual to individual or from study to study, within a certain domain and following a uniform pattern.

Usage

GPW.logrank(data, obs.time, time.to.event, event.status, trt.group, tl, tu) 

Arguments

data

Data frame

obs.time

Column name in data for the observational time.

time.to.event

Column name in data for the event time.

event.status

Column name in data for the event status, where 0 denotes being censored, and 1 denotes events.

trt.group

Column name in data for the treatment group, where 0 denotes controls, and 1 denotes treated subjects.

tl

Lower bound of delayed duration domain

tu

Upper bound of delayed duration domain

Value

The p-value of the test.

Author(s)

Zhenzhen Xu <[e-mail]> , Boguang Zhen<[e-mail]>, Yongsoek Park <[e-mail]> and Bin Zhu <[e-mail]>

References

Xu, Z., Park, Y., Zhen, B. & Zhu, B. (2017). Achieving optimal power of logrank test with random treatment time-lag effect. Biometrika. Under review.

Xu, Z., Zhen, B., Park, Y., & Zhu, B. (2017). Designing therapeutic cancer vaccine trials with delayed treatment effect. Statistics in medicine, 36(4), 592-605.

See Also

pow.SEPPLE.plus

Examples

  data(data, package="DelayedEffect.Design")
  GPW.logrank(data, "X", "time_to_event", "event_status", "Z", 30, 30*11)