facetsviz

Overview

facetsviz is an R package for parsing FACETS .out files and producing reusable diagnostic visualizations from multi-facet Rasch measurement output. It provides a suite of functions to easily create beautiful, publication-ready plots using ggplot2.

• plot_wright()
• plot_probability()
• plot_distribution()
• plot_usage()
• plot_fairness()

library(facetsviz)

facets <- read_facets("peerAssessment.out")
plot_wright(facets)

Installation

# Install from local source
install.packages("facetsviz_0.1.1.tar.gz", repos = NULL, type = "source")

# Or using devtools from GitHub
devtools::install_github("myprabowo/facetsviz")

Usage

facetsviz provides R functions for reading data, plotting, batch rendering, and an interactive Shiny app.

library(facetsviz)

# 1. Read FACETS output
facets <- read_facets("peerAssessment.out")

# 2. Inspect available measurement reports
names(facets$measurement_reports)

# 3. Create individual plots
plot_wright(facets)
plot_probability(facets)

# 4. Render all diagnostic plots to a folder
render_plots(facets, output_dir = "figures", formats = "png")

# 5. Launch the interactive Shiny app
facetsviz::run_app()

Examples

Use the plotting functions to inspect your Rasch measurement data:

• plot_wright(facets): Visualizes person measures and item difficulties on a common logit scale.
• plot_probability(facets): Shows category probability curves.
• plot_distribution(facets): Displays the distribution of measures for a specific facet.
• plot_usage(facets): Shows how rating scale categories are used.