simtrial (version 1.0.0)

ex1_delayed_effect: Time-to-event data example 1 for non-proportional hazards working group

Description

Survival objects reverse-engineered datasets from published Kaplan-Meier curves. Individual trials are de-identified since the data are only approximations of the actual data. Data are intended to evaluate methods and designs for trials where non-proportional hazards may be anticipated for outcome data.

Usage

data(ex1_delayed_effect)

Format

Data frame with 4 variables:

• id: Sequential numbering of unique identifiers.

• month: Time-to-event.

• event: 1 for event, 0 for censored.

• trt: 1 for experimental, 0 for control.

References

Lin, Ray S., Ji Lin, Satrajit Roychoudhury, Keaven M. Anderson, Tianle Hu, Bo Huang, Larry F Leon, Jason J.Z. Liao, Rong Liu, Xiaodong Luo, Pralay Mukhopadhyay, Rui Qin, Kay Tatsuoka, Xuejing Wang, Yang Wang, Jian Zhu, Tai-Tsang Chen, Renee Iacona & Cross-Pharma Non-proportional Hazards Working Group. 2020. Alternative analysis methods for time to event endpoints under nonproportional hazards: A comparative analysis. Statistics in Biopharmaceutical Research 12(2): 187--198.

See Also

ex2_delayed_effect, ex3_cure_with_ph, ex4_belly, ex5_widening, ex6_crossing

Examples

library(survival)

data(ex1_delayed_effect)
km1 <- with(ex1_delayed_effect, survfit(Surv(month, evntd) ~ trt))
km1
plot(km1)
with(subset(ex1_delayed_effect, trt == 1), survfit(Surv(month, evntd) ~ trt))
with(subset(ex1_delayed_effect, trt == 0), survfit(Surv(month, evntd) ~ trt))