Plot a sensitivity curve

sensitivity-curve.R

# Create sensitivity curve of coefficient estimates
library(tidyverse)
library(cowplot)
library(fastDummies)

# Setup ----
rm(list = ls())
theme_set(theme_cowplot())
set.seed(42)

# Create some fake estimates to plot ----
# Required components: est, se, and any variables that describe specifications

# These are the possible specifications we "estimated"
fe <- c("Unit", "Time", "Unit + Time")
controls <- c("Basic", "Some", "Full")

estimates <- as_tibble(expand.grid(`Fixed Effects` = fe, `Controls` = controls))
estimates <- estimates %>% mutate(est = rnorm(n()), se = runif(n(), 0, 0.1))

# Create a plot of the estimates ----
spec_cols <- c("Fixed Effects", "Controls") # Could be set by user or figured out
# Note: This assumes the preferred ordering of the specification categories is the order in which they are given

estimates <- estimates %>% mutate(ci_l = est - 1.96 * se, ci_h = est + 1.96 * se)

estimates <- estimates %>% 
    arrange(est) %>% mutate(h_order = 1:n()) # Sort on point estimates for horizontal ordering

coef_plot <- ggplot(estimates, aes(x = h_order, y = est)) + 
    geom_linerange(aes(ymin = ci_l, ymax = ci_h), size = 1, alpha = 0.5) + 
    geom_point(fill = "white", shape = 21) + 
    labs(y = "Coefficient") + 
    theme(axis.title.x = element_blank(), axis.ticks.x = element_blank(), axis.line.x = element_blank(), axis.text.x = element_blank())

# Create a plot of the specifications ----
# Function to create a specification plot for a single category. 
make_spec_plot <- function(category) {
    # category = spec_cols[1] # DEBUG
    specs <- dummy_cols(estimates, select_columns = category, remove_selected_columns = T) %>%
        select(h_order, starts_with(category)) %>% 
        pivot_longer(starts_with(category), names_prefix = paste0(category, "_")) %>%
        mutate(name = factor(name, levels = rev(unique(name)))) 
    
    spec_plot <- ggplot(specs, aes(x = h_order, y = name, alpha = value)) +
        geom_point() + 
        scale_alpha_continuous(guide = FALSE) +
        theme(axis.title.x = element_blank(), axis.ticks.x = element_blank(), axis.line.x = element_blank(), axis.text.x = element_blank()) + 
        theme(axis.text.y = element_text(size = 6), axis.title.y = element_blank(), axis.ticks.y = element_blank(), axis.line.y = element_blank())
    spec_plot    
}
spec_plots <- lapply(spec_cols, make_spec_plot)

combined_plot <- plot_grid(plotlist = c(list(coef_plot), spec_plots), 
          labels = c("", spec_cols), label_size = 8, label_fontface = "italic", vjust = 0.5, hjust = -0.1,
          rel_heights = c(1, 0.2, 0.2), ncol = 1, align = "v")

save_plot("sensitivity-curve.png", combined_plot)