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MonotoneeHazardRatio is a tool for nonparametric estimation and inference for a monotone non-decreasing hazard ratio, based on the work “Nonparametric inference under a monotone hazard ratio order” by Y. Wu and T. Westling (2022) <arXiv:2205.01745>.
Our packages needs the following packages to work.
library(survival)
library(fdrtool)
library(KernSmooth)It is staightforward to use this package. First you need to import
the data (optional: split the data into two groups “S” and “T” such that
the hazard ratio \(\lambda_S/\lambda_T\) is non-decreasing).
Pass the dataframes along with the evaluation grid to the function
monotoneHR(), which takes \(\alpha =0.05\) as the default confidence
level, to have the hazard ratio and its confidence intervals
estimated.
As shown in the example, we are going to estimate a non-decreasing
hazard ratio using the example data survData. The estimated
hazard ratio is stored in theta$hr, while the confidence
intervals are stored in theta$ci.lower and
theta$ci.upper.
library(MonotoneHazardRatio)
### Use the example data in the package
data(survData)
### split it into two dataframes
s.data <- survData[survData$group == 'S']
t.data <- survData[survData$group == 'T']
### Evaluation grid
t.grid <- seq(0, 10, 1)
### Estimation and inference
theta <- monotoneHR(t.grid, s.data, t.data)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.