A tool for drawing sassy 'UML' (Unified Modeling Language) diagrams 
  based on a simple syntax, see <https://www.nomnoml.com>. Supports styling, 
  R Markdown and exporting diagrams in the PNG format. Note: you need a chromium based 
  browser installed on your system.

A nomogram can not be easily applied,
    because it is difficult to calculate the points or even the survival probability.
  The package, including a function of nomogramEx(),
    is to extract the polynomial equations to calculate the points of each variable,
    and the survival probability corresponding to the total points.

Runs several heterogeneity-robust difference-in-differences (DID) event-study estimators
    for non-absorbing (i.e., treatment can switch on and off over time, allowing treatment reversal)
    binary treatments through their respective packages,
    harmonizes their output onto a common time axis and tidy data structure, and overlays them in a single
    'ggplot2' panel for visual comparison. 
    Supported estimators include those provided by 'DIDmultiplegtDYN', 'PanelMatch', and 'fect', with an 
    optional naive two-way fixed-effects reference series via 'fixest'. The underlying methods are respectively described in
    Clement de Chaisemartin and Xavier D'Haultfoeuille. "Difference-in-Differences Estimators of Intertemporal Treatment Effects."
    The Review of Economics and Statistics (2026) <doi:10.1162/rest_a_01414>,
    Kosuke Imai, In Song Kim, and Erik H. Wang. "Matching methods for causal inference with time‐series cross‐sectional data." 
    American Journal of Political Science 67.3 (2023) <doi:10.1111/ajps.12685>,
    Licheng Liu, Ye Wang, and Yiqing Xu. "A practical guide to counterfactual estimators for causal inference
    with time‐series cross‐sectional data." American Journal of Political Science 68.1 (2024) <doi:10.1111/ajps.12723>, and
    Laurent R. Bergé, Kyle Butts, and Grant McDermott. "Fast and user-friendly econometrics estimations: The R package 'fixest'."
    arXiv preprint (2026) <doi:10.48550/arXiv.2601.21749>.
    A single nabs_event_study() wrapper runs any supported estimator with a common interface;
    nabs_event_study_simple() provides a one-line front door for quick exploratory runs;
    the S3 generic as_nabs_event_study() coerces estimator output into a tidy stable schema;
    and nabs_event_plot() overlays multiple methods on a single 'ggplot2' panel, with optional naive two-way
    fixed effects drawn in a neutral color as a reference.