Visualizing Causal Assignment Trees for CSDiD and DR-DDD Designs R package catviz version 0.1.1 Tools for constructing, labeling, and visualizing Causal Assignment Trees (CATs) in settings with staggered adoption. Supports Callaway and Sant'Anna difference-in-differences (CSDiD) and doubly robust difference-in-difference-differences (DR-DDD) designs. The package helps clarify treatment timing, never-treated vs. not-yet-treated composition, and subgroup structure, and produces publication-quality diagrams and summary tables. Current functionality focuses on data-to-node mapping, node counts, cohort-year summaries, and high-quality tree plots suitable for empirical applications prior to estimation. Methods are based on Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>, Sant'Anna and Zhao (2020) <doi:10.1016/j.jeconom.2020.06.003>, and Kilanko (2026) <https://github.com/VictorKilanko/catviz>. Software Depends: R (>= 4.1.0) Imports: dplyr, ggplot2, glue, tidyr, purrr, tibble, grid, rlang Suggests: testthat (>= 3.0.0) Victor Kilanko <victorkilanko@gmail.com> Comprehensive R Archive Network (CRAN) Victor Kilanko [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=catviz/LICENSE) 2026-04-01 application/tgz https://CRAN.R-project.org/package=catviz doi:10.32614/CRAN.package.catviz