Assessing Cure Model Appropriateness for Survival Data R package cureAssess version 0.1.0 Assesses whether cure models are appropriate for right-censored survival data, where a fraction of subjects may never experience the event of interest. Implements a two-stage workflow combining Kaplan-Meier visualization and comparison of parametric cure and non-cure models by the Akaike information criterion with formal diagnostics for sufficient follow-up and for the presence of a cured fraction. The diagnostics include the statistics of Maller and Zhou (1992) <doi:10.1093/biomet/79.4.731> and Maller and Zhou (1994) <doi:10.1080/01621459.1994.10476889>, the test of Shen (2000) <doi:10.1016/S0167-7152(00)00063-8>, and the ratio estimation of censored uncured subjects ('RECeUS') method of Selukar and Othus (2023) <doi:10.1002/sim.9610>. Software Depends: R (>= 4.1.0) Imports: survival, flexsurv, flexsurvcure, survminer, ggplot2, dplyr, stats Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Geethanjalee Mudunkotuwa <geethanjaleem@gmail.com> Comprehensive R Archive Network (CRAN) Geethanjalee Mudunkotuwa [aut, cre, cph], Durbadal Ghosh [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=cureAssess/LICENSE) 2026-09-14 application/tgz https://CRAN.R-project.org/package=cureAssess doi:10.32614/CRAN.package.cureAssess en-US