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Plot Estimates from a Table of Results

Source: R/plot_estimates.R
plot_estimates.Rd

This function creates a ggplot object visualizing logistic regression coefficients with their 95% confidence intervals. Significant markers are highlighted based on a specified p-value threshold.

Usage

plot_estimates(
  tbl,
  sig = 0.05,
  sig_colors = c(`FALSE` = "grey", `TRUE` = "blue4"),
  x_title = "Coefficient (95% CI)",
  y_title = "Variant",
  title = NULL,
  axis_label_size = 9,
  marker_order = NULL
)

Arguments

tbl

A data frame or tibble containing the logistic regression results. Expected columns are:

  • marker: The name of the marker (e.g., variable name).

  • pval: The p-value for each marker.

  • ci.lower: The lower bound of the confidence interval.

  • ci.upper: The upper bound of the confidence interval.

  • est: The estimated coefficient.

sig

(optional) The significance threshold for p-values. Defaults to 0.05.

sig_colors

(optional) A vector of two colors to represent significant and non-significant estimates.

x_title

(optional) The title for the x-axis. Defaults to "Coefficient (95% CI)".

y_title

(optional) The title for the y-axis. Defaults to "Variant".

title

(optional) The main title of the plot. If NULL, no title is added.

axis_label_size

(optional) The font size of the axis labels. Defaults to 9.

marker_order

(optional) Vector indicating the order of the markers to be plotted on the y-axis.

Value

A ggplot object showing the logistic regression coefficients with confidence intervals. Significant markers (p-value < sig) are colored differently.

Examples

# Example dataset
tbl <- tibble::tibble(
  marker = c("(Intercept)", "var1", "var2", "var3"),
  pval = c(0.1, 0.03, 0.2, 0.04),
  ci.lower = c(-0.2, 0.1, -0.3, 0.2),
  ci.upper = c(0.5, 0.8, 0.4, 1.1),
  est = c(0.2, 0.5, 0.1, 0.7)
)

# Plot
plot_estimates(tbl)