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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.
Health stats visible at Monitor.