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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.
library(citsr)
The package includes a built-in simulated dataset named df_cits_example.
data("df_cits_example", package = "citsr") head(df_cits_example)
res <- cits( data = df_cits_example, y_col = "y", T_col = "T", I_col = "I", E_col = "E" ) summary(res$model)
plot_fitted <- plot_cits_result( res, y_col = "y", T_col = "T", E_col = "E" ) plot_fitted
plot_cf <- plot_cits_result_cf( res, y_col = "y", T_col = "T", I_col = "I", E_col = "E", intervention_time = 50 ) plot_cf
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