MonotoneHazardRatio (version 0.1.1)

monotoneHR: Estimate a non-decreasing hazard ratio function, together with a 100(1-\(\alpha\))% confidence interval

Description

Estimate a non-decreasing hazard ratio function, together with a 100(1-\(\alpha\))% confidence interval

Usage

monotoneHR(time.grid, S.data, T.data, ci.lvl = 0.05)

Value

hr The estimated hazard ratio

tau The estimated scaled parameter of the limiting Chernoff distribution

ci.upper and ci.lower are the upper bound and lower bound of the estimated confidence interval

Arguments

time.grid

A vector on which the hazard ratio function to be evaluated

S.data

A dataframe containing observed survival time and censoring, it corresponds to the hazard function on the numerator

T.data

A dataframe containing observed survival time and censoring, it corresponds to the hazard function on the demoninator

ci.lvl

A number that specify the confidence level \(\alpha\). Default is 0.05.

Examples

# load the example data
data(survData)
# load the computed Chernoff distribution
data("chernoff_realizations")
# split the data into two groups S and T, make sure that the column of survival time
# is named as "time", and the column of censoring named as "status" (0 as being censored)
s.data <- survData[survData$group == 'S',]
t.data <- survData[survData$group == 'T',]
# define the evaluation grid on which the hazard ratio function is to be computed
t.grid <- seq(0, 10, 1)
# estimation and inference of the non-decreasing hazard ratio (defined as
#\eqn{\lambda_S}/\eqn{\lambda_T}, where \eqn{\lambda} is the hazard function) function
theta <- monotoneHR(t.grid, s.data, t.data)