While-Alive Regression for Composite Endpoints with Cluster-Robust Inference R package WAreg version 0.1.0 Provides estimation and inference for while-alive regression models targeting the while-alive loss rate for composite endpoints that include recurrent events and a terminal event. The implementation supports flexible time-varying covariate effects through user-selected time bases, including B-splines, natural splines, M-splines, step functions, truncated linear bases, interval-local bases, and piecewise polynomials. Inference can be performed using cluster-robust variance estimators for cluster-randomized trials, with subject-level (IID) variance as a special case. The package includes prediction and plotting utilities and K-fold cross-validation for selecting basis and tuning parameters. Methodology is based on Fang et al. (2025) <doi:10.1093/biostatistics/kxaf047>. Software Depends: R (>= 4.1) Imports: dplyr, tidyr, tibble, ggplot2, survival, nleqslv, splines, MASS, magrittr, rlang Suggests: splines2, testthat (>= 3.0.0), knitr, rmarkdown Xi Fang <x.fang@yale.edu> Comprehensive R Archive Network (CRAN) Xi Fang [aut, cre], Hajime Uno [aut], Fan Li [aut] GPL-3 2026-03-06 application/tgz https://CRAN.R-project.org/package=WAreg doi:10.32614/CRAN.package.WAreg