A coefficient plot displays regression coefficients as points positioned along a horizontal axis, with horizontal error bars showing confidence intervals. This visualization makes it easy to assess effect sizes and statistical significance - coefficients whose confidence intervals cross zero are not statistically significant. Typically used to summarize results from linear, logistic, or other regression models in a clear, publication-ready format.
#' anyplot.ai
#' coefficient-confidence: Coefficient Plot with Confidence Intervals
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 91/100 | Created: 2026-05-18
library(ggplot2)
library(dplyr)
library(ragg)
set.seed(42)
# --- Theme tokens -----------------------------------------------------------
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
IMPRINT <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477")
# --- Data -------------------------------------------------------------------
# Simulated housing price regression coefficients with confidence intervals
coefficients <- data.frame(
variable = c("Square Footage", "Bedrooms", "Bathrooms", "Age",
"Lot Size", "Garage Spaces", "Distance to School",
"Property Tax Rate", "Basement Area", "Year Built"),
coefficient = c(0.85, 0.42, -0.18, -0.15, 0.28, 0.35, -0.52, -0.08, 0.22, 0.12),
ci_lower = c(0.72, 0.28, -0.35, -0.29, 0.15, 0.21, -0.68, -0.22, 0.08, -0.05),
ci_upper = c(0.98, 0.56, -0.01, -0.01, 0.41, 0.49, -0.36, 0.06, 0.36, 0.29),
significant = c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, FALSE)
) %>%
# Order by coefficient magnitude (descending)
arrange(desc(abs(coefficient))) %>%
mutate(variable = factor(variable, levels = variable))
# --- Plot -------------------------------------------------------------------
p <- ggplot(coefficients, aes(x = coefficient, y = variable,
color = significant, fill = significant)) +
# Reference line at zero
geom_vline(xintercept = 0, linetype = "solid", color = INK_SOFT,
linewidth = 0.5, alpha = 0.5) +
# Confidence interval error bars
geom_errorbarh(aes(xmin = ci_lower, xmax = ci_upper),
height = 0.3, linewidth = 1.2, alpha = 0.8) +
# Coefficient points
geom_point(size = 5, alpha = 0.9) +
# Color scale: significant vs non-significant
scale_color_manual(
name = "Statistically Significant",
values = c("TRUE" = IMPRINT[1], "FALSE" = INK_SOFT),
labels = c("TRUE" = "Yes", "FALSE" = "No")
) +
scale_fill_manual(
name = "Statistically Significant",
values = c("TRUE" = IMPRINT[1], "FALSE" = INK_SOFT),
labels = c("TRUE" = "Yes", "FALSE" = "No")
) +
labs(
title = "coefficient-confidence · r · ggplot2 · anyplot.ai",
x = "Coefficient Estimate",
y = "Predictor Variable"
) +
theme_minimal(base_size = 14) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid.major = element_line(color = INK, linewidth = 0.2),
panel.grid.minor = element_blank(),
axis.title = element_text(color = INK, size = 20),
axis.text = element_text(color = INK_SOFT, size = 16),
axis.text.y = element_text(color = INK_SOFT, size = 16),
plot.title = element_text(color = INK, size = 24, face = "plain"),
legend.position = "bottom",
legend.background = element_rect(fill = PAGE_BG, color = NA),
legend.text = element_text(color = INK_SOFT, size = 16),
legend.title = element_text(color = INK, size = 18)
)
# --- Save -------------------------------------------------------------------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 16,
height = 9,
units = "in",
dpi = 300
)
Part of Coefficient Plot with Confidence Intervals on anyplot.ai.