ahr_from_km: Average Hazard Estimation based on Kaplan-Meier Estimates

In bonsaiforest: Shrinkage Based Forest Plots

Average Hazard Estimation based on Kaplan-Meier Estimates

Description

Average Hazard Estimation based on Kaplan-Meier Estimates

Usage

ahr_from_km(resp, trt, data, status, t_quantile = 0.99)

Arguments

resp	(string) the response variable name.
trt	(string) the treatment variable name. The treatment variable must be a factor with 2 levels where the first level is the control and the second one the treatment.
data	(⁠data frame⁠) the data frame with the variables.
status	(string) the status variable name in survival data.
t_quantile	(number) definition of the quantile.

Details

Estimates can be unstable due to the variability of the Kaplan-Meier estimates in the tails. The t_quantile argument can address this, e.g. by setting it to 0.95, the 5% highest times will be discarded. By default, the 1% highest times are discarded.

Value

The estimated average hazard ratio of the treatment (second level of trt) versus the control (first level of trt).

Examples

ahr_from_km("tt_pfs", "arm", example_data, "ev_pfs")
ahr_from_km("tt_pfs", "arm", example_data, "ev_pfs", t_quantile = 0.95)

bonsaiforest documentation built on Sept. 30, 2024, 9:46 a.m.