EffectVisR

Overview

The EffectVisR package provides functions to easily visualise effect sizes and their 95% confidence intervals. It offers two flexible plotting functions, each tailored to highlight confidence intervals in different ways:

• es_plot_v1: Highlights confidence intervals with distinct gradient colours.
• es_plot_v2: Emphasises the closeness of confidence intervals to the effect size using gradient shading.

Both functions are highly customisable and are ideal for presentations and publications.

Key Features:

• Two visualisation methods:

  • es_plot_v1: Shades the confidence interval with different colours for the lower and upper bounds.

  • es_plot_v2: Shades the confidence interval with lighter colours further from the effect size.

• Customisable visuals:

  • Multiple colour palettes ("viridis", "grey", "magma", etc.).

  • Adjustable axis labels, titles, and arrow styles.

  • Option to display the confidence interval as a full fan or partial arc.

• Export options: Save plots as high-quality PNG files with transparent backgrounds.

Installation

To install the latest version of EffectVisR from GitHub, use the following commands in R:

install.packages("remotes")

remotes::install_github("FSchwendinger/EffectVisR")

After installation, load the package using:

library(EffectVisR)

Example Usage

1. Visualising effect sizes with es_plot_v1

The es_plot_v1 function creates a plot with a gradient showing confidence intervals around an effect size. It highlights the range of possible effect sizes (95% CI) using colour gradients, with different colours for positive and negative effect sizes.

library(EffectVisR)

# Define the effect size and confidence intervals
effect_size <- 0.4
ci_lower <- 0.1
ci_upper <- 0.7

# Create the plot
EffectVisR::es_plot_v1(
  effect_size = effect_size,
  ci_lower = ci_lower,
  ci_upper = ci_upper,
  palette = "viridis",
  arrow_color = "black",
  axis_title_size = 8,
  axis_label_size = 8
)

2. Visualising effect sizes with es_plot_v2

The es_plot_v2 function generates a plot with shading that highlights the confidence interval range and how close it is to the effect size. Darker colours within the 95% CI show that the values are close to the estimate, while lighter colours are further away.This will produce plots like the following.

# Define effect size and confidence interval
effect_size <- -0.3
ci_lower <- -0.6
ci_upper <- 0

# Create plot 1
a = EffectVisR::es_plot_v2(
  effect_size = effect_size,
  ci_lower = ci_lower,
  ci_upper = ci_upper,
  palette = "grey",
  arrow_color = "darkred",
  axis_title_size = 8,
  axis_label_size = 8
)

# Create plot 2
b = EffectVisR::es_plot_v2(
  effect_size = effect_size,
  ci_lower = ci_lower,
  ci_upper = ci_upper,
  palette = "magma",
  axis_title_size = 8,
  axis_label_size = 8,
  area_arc = 0.95
)

cowplot::plot_grid(a, b, nrow = 1)

Customisation Options

Both functions (es_plot_v1 and es_plot_v2) allow you to adjust several parameters:

• effect_size: Numeric value indicating the estimated effect size.

• ci_lower, ci_upper: Lower and upper bounds of the 95% confidence interval.

• palette: Choose from "viridis", "grey", or other Viridis-based palettes (e.g., "magma", "plasma", etc.).

• arrow_color: Customise the colour of the arrow representing the effect size.

• area_arc: Switch between fan and arch to display 95% confidence intervals.

• save_path: Option to save the plot as a PNG file (optional).

• axis_title_size, axis_label_size: Adjust font sizes for axis titles and labels.

• limit: Set the limits of effect sizes displayed in the plot.

Example: Saving the Plot

You can save your plot with a transparent background using the save_path argument.

EffectVisR::es_plot_v1(
  effect_size = 0.4,
  ci_lower = 0.1,
  ci_upper = 0.7,
  palette = "viridis",
  arrow_color = "black",
  save_path = "effect_size_plot.png"
)

License

This package is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. You are free to use, share, and modify the work for non-commercial purposes, provided that appropriate credit is given. See the LICENSE file for more information.

For more details, see Creative Commons BY-NC 4.0.

Citation

If you use this R-package, please cite it as follows:

Schwendinger, F., & Lichtenstein, E. (2024). EffectVisR - Customisable effect size plots with confidence intervals for scientific presentations and publications (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.14544022

Contributors

• Fabian Schwendinger, PhD (author, creator)

• Eric Lichtenstein, PhD (author)

• Denis Infanger, PhD (contributor)

Feel free to contribute or report any issues on the GitHub repository.