Author: Hanmin Gu
Date: 2025-12-17

# citsr Package Examples

#### Hanmin Gu

#### 2025-12-17

# Overview

This vignette demonstrates how to use the `citsr` package for conducting Controlled Interrupted Time Series (CITS) analysis. The package provides functions for model fitting using generalized least squares (GLS), visualizing fitted trajectories with confidence intervals, and generating counterfactual predictions for treatment groups.

# 1. Example Data

The package includes a built-in simulated dataset named `df_cits_example`.

    data("df_cits_example", package = "citsr")
    head(df_cits_example)

C:368029e7d2d_examples.R

# 2. Fit CITS Model

    res <- cits(
      data = df_cits_example,
      y_col = "y",
      T_col = "T",
      I_col = "I",
      E_col = "E"
    )

    summary(res$model)

C:368029e7d2d_examples.R

# 3. Visualize Fitted Values with 95% Confidence Intervals

    plot_fitted <- plot_cits_result(
      res,
      y_col = "y",
      T_col = "T",
      E_col = "E"
    )
    plot_fitted

C:368029e7d2d_examples.R

# 4. Visualize Counterfactual Trajectory for Treatment Group

    plot_cf <- plot_cits_result_cf(
      res,
      y_col = "y",
      T_col = "T",
      I_col = "I",
      E_col = "E",
      intervention_time = 50
    )
    plot_cf

C:368029e7d2d_examples.R