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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)# 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")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()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.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.