R/survAH-package.R

In survAH: Survival Data Analysis using Average Hazard

#' @name survAH-package
#' @aliases  survAH-package
#' @title Survival Data Analysis using Average Hazard
#' @description The survAH package performs two-sample comparisons based on average hazard with survival weight (AHSW) or general censoring-free incidence rate (CFIR) proposed by Uno and Horiguchi (2023) <doi:10.1002/sim.9651>.
#' @author Hajime Uno, Miki Horiguchi, Zihan Qian
#' @references 
#' Uno H and Horiguchi M. Ratio and difference of average hazard with survival weight: new measures to quantify survival benefit of new therapy. Statistics in Medicine. 2023; 42(7):936-952. <doi:10.1002/sim.9651>

#' Uno H, Tian L, Horiguchi M, Hattori S, Kehl KL. Regression models for average hazard. Biometrics. 2024; 80(2):ujae037. <doi: 10.1093/biomtc/ujae037>

#' Horiguchi M, Tian L, Kehl KL, Uno H. Assessing delayed treatment benefits of immunotherapy using long-term average hazard: a novel test/estimation approach. Lifetime Data Anal. 2025; 31(4):784-809. <doi:10.1007/s10985-025-09671-0>

#' Qian Z, Tian L, Horiguchi M, Uno H. A novel stratified analysis method for testing and estimating overall treatment effects on time-to-event outcomes using average hazard with survival weight. Stat Med. 2025; 44(7):e70056. <doi:10.1002/sim.70056>

#' @seealso
#' survival survRM2 surv2sampleComp
#' @importFrom stats pnorm qnorm as.formula model.frame model.matrix model.response
#' @importFrom utils data
#' @importFrom survival survfit coxph
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