Package: catviz
Title: Visualizing Causal Assignment Trees for CSDiD and DR-DDD Designs
Version: 0.1.1
Authors@R: 
    person("Victor", "Kilanko", email = "victorkilanko@gmail.com", role = c("aut", "cre"))
Description: 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>.
License: MIT + file LICENSE
URL: https://github.com/VictorKilanko/catviz
BugReports: https://github.com/VictorKilanko/catviz/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, glue, tidyr, purrr, tibble, grid, rlang
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-03-27 19:13:26 UTC; victo
Author: Victor Kilanko [aut, cre]
Maintainer: Victor Kilanko <victorkilanko@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:00:20 UTC
