Creates comprehensive DiD visualization showing parallel trends, treatment effects, and robustness checks. Includes pre-post comparison and treatment-control evolution over time.
Usage
plot_did_results(
did_results,
plot_type = "trends",
outcome_vars = NULL,
show_treatment_period = TRUE,
parallel_trends_test = TRUE,
use_bw = FALSE,
line_size = 1.2,
point_size = 3,
ribbon_alpha = 0.3,
ncol = 2,
y_limits = NULL
)Arguments
- did_results
List. Output from difference_in_differences() function
- plot_type
Character. Type of plot: "trends", "effects", "robustness", "all". Default: "trends"
- outcome_vars
Character vector. Outcomes to plot. Default: NULL (all outcomes)
- show_treatment_period
Logical. Highlight treatment period. Default: TRUE
- parallel_trends_test
Logical. Show parallel trends test results. Default: TRUE
- use_bw
Logical. Use black and white theme. Default: FALSE
- line_size
Numeric. Size of trend lines. Default: 1.2
- point_size
Numeric. Size of points. Default: 3
- ribbon_alpha
Numeric. Transparency for confidence ribbons. Default: 0.3
- ncol
Integer. Number of columns for multiple outcomes. Default: 2
- y_limits
Numeric vector. Y-axis limits. Default: NULL (automatic)
Examples
if (FALSE) { # \dontrun{
# Basic DiD trends plot
did_plot <- plot_did_results(
did_results = did_estimation_results,
plot_type = "trends",
show_treatment_period = TRUE
)
# Treatment effects plot
effects_plot <- plot_did_results(
did_results = did_estimation_results,
plot_type = "effects",
use_bw = TRUE
)
} # }