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ShinyItemAnalysis

Test and item analysis via shiny

Overview

ShinyItemAnalysis is an R package including functions and interactive shiny application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters. Offered methods include:

  • Exploration of total and standard scores
  • Analysis of correlation structure and validity
  • Analysis of measurement error and reliability
  • Traditional item analysis
  • Item analysis with regression models
  • Item analysis with IRT models
  • Detection of differential item functioning
  • ... and more via add-on modules

Number of toy datasets is available, the interactive application also allows the users to upload and analyze their own data and to automatically generate PDF or HTML reports.

ShinyItemAnalysis is available online at Czech Academy of Sciences and shinyapps.io. It can be also downloaded from CRAN. Visit our web page about ShinyItemAnalysis to learn more!

Installation

The easiest way to get ShinyItemAnalysis is to install it from CRAN:

install.packages("ShinyItemAnalysis")
install.packages("ShinyItemAnalysis", dependencies = TRUE)

Or you can get the newest development version from GitHub:

if(!require(remotes)) install.package("remotes")
remotes::install_github("patriciamar/ShinyItemAnalysis")

Version

The table below summarizes the currently available versions of ShinyItemAnalysis across different distribution sources, distinguishing between sources that provide both the R package and the Shiny application and those that provide the application only.

SourceTypeVersion
CRANPackage & App1.6.0
GitHub (development)Package & App1.6.0
Czech Academy of SciencesOnline app only1.6.0
shinyapps.ioOnline app only1.6.0

Usage

It is very easy to run ShinyItemAnalysis in R:

ShinyItemAnalysis::run_app()
# or
ShinyItemAnalysis::startShinyItemAnalysis()

Or if you are an RStudio IDE user, simply click on Run ShinyItemAnalysis in Addins menu (located at the end of the toolbar). Last but not least, you can also try the app directly online at Czech Academy of Sciences or shinyapps.io!

References

When using ShinyItemAnalysis software, we appreciate if you include a reference in your publications. To cite the software, please, use:

Martinková P., & Hladká A. (2023) Computational Aspects of Psychometric Methods: With R. (1st ed.). Chapman and Hall/CRC. doi: 10.1201/9781003054313. ISBN 9781003054313.

Martinková P., & Drabinová A. (2018) ShinyItemAnalysis for teaching psychometrics and to enforce routine analysis of educational tests. The R Journal, 10(2), 503-515. doi: 10.32614/RJ-2018-074.

When using one of the SIA modules, please, cite:

Martinková P., Netík J. & Hladká A. (2026) Enhancing Psychometric Analysis with Interactive SIA Modules. Psychometrika, Online First, 1-29. doi: 10.1017/psy.2026.10088.

Getting help and providing feedback

If you meet any issue with ShinyItemAnalysis interactive application or its modules, contact us directly at sia-group@cs.cas.cz. In case you meet any trouble with ShinyItemAnalysis R package, please report as an issue on GitHub. We warmly encourage you to provide your feedback using the Google form.

License

This program is free software and you can redistribute it and or modify it under the terms of the GNU GPL 3.

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Version

Install

install.packages('ShinyItemAnalysis')

Monthly Downloads

1,029

Version

1.6.0

License

GPL-3

Maintainer

Patricia Martinkova

Last Published

June 8th, 2026

Functions in ShinyItemAnalysis (1.6.0)

HCIprepost

Homeostasis concept inventory pretest and posttest scores
NIH

NIH grant peer review scoring dataset
TestAnxietyCor

Correlation matrix for the test anxiety dataset
ShinyItemAnalysis_options

Options consulted by ShinyItemAnalysis
ItemAnalysis

Compute traditional item analysis indices
ShinyItemAnalysis-package

ShinyItemAnalysis: Test and Item Analysis via Shiny
MSclinical

Clinical outcomes in multiple sclerosis patients dataset
MSATB

Dichotomous dataset of Medical School Admission Test in Biology.
LearningToLearn

Dichotomous dataset of learning to learn test
ICCrestricted

Range-restricted reliability with intra-class correlation
HeightInventory

Height inventory dataset
blis2blirt

Reparametrize fitted BLIS model to IRT
coef,BlisClass-method

Get Coefficients from a fitted BLIS model
fa_parallel

Conduct Parallel Analysis
cronbach_alpha

Compute Cronbach alpha with confidence interval
dataMedical

Dichotomous dataset of admission test to medical school
delta_ses

Get standard errors using delta method approximation
fit_blis

Fit Baseline-category Logit Intercept-Slope (BLIS) model on nominal data
dataMedicalgraded

Graded dataset of admission test to medical school
dataMedicaltest

Dataset of admission test to medical school
dataMedicalkey

Key of correct answers for dataset of admission test to medical school
plotDIFLogistic

Function for characteristic curve of 2PL logistic DIF model
plotAdjacent

Plot category probabilities of adjacent category logit model
plotCumulative

Plot cumulative and category probabilities of cumulative logit model
obtain_nrm_def

Obtain model definition for mirt's nominal model taking in account the key of correct answers
plot.sia_parallel

Plot Method for Parallel Analysis Output
nominal_to_int

Turn nominal (factor) data to integers, keep original levels with a key of correct responses alongside
ggWrightMap

Plot person-item map (Wright map) using ggplot2
get_orig_levels

Get Original Levels from a Fitted BLIS model
plotDIFirt

Plot item characteristic curve of DIF IRT model
gDiscrim

Compute generalized item discrimination
startShinyItemAnalysis

Start ShinyItemAnalysis application
recode_nr

Recognize and recode not-reached responses
print.blis_coefs

Print method for BLIS coefficients
theme_app

Complete theme for ShinyItemAnalysis graphics
plot_corr

Compute and plot an item correlation matrix
plotMultinomial

Plot category probabilities of multinomial model
remove_empty_cols

Remove columns that are empty
plotDistractorAnalysis

Plot item distractor analysis
CLoSEread6

Czech Longitudinal Study in Education (CLoSE) - reading in 6th grade
DDplot

Plot difficulties and discriminations/item validity
DistractorAnalysis

Distractor analysis
BlisClass-class

BLIS S4 class
GMAT

Dichotomous dataset based on GMAT with the same total score distribution for groups.
HCIkey

Key of correct answers for homeostasis concept inventory dataset
HCI

Homeostasis Concept Inventory dichotomous dataset
HCIlong

Homeostasis Concept Inventory in a long format
AttitudesExpulsion

Attitudes towards the Expulsion of the Sudeten Germans (dataset)
AIBS

AIBS grant peer review scoring dataset
HCIdata

Homeostasis concept inventory full dataset
CZmaturaS

CZmatura dataset - sample
EPIA

The Eysenck Personality Inventory Impulsivity Subscale
Anxiety

PROMIS Anxiety Scale Dataset
CZmatura

CZmatura dataset
BFI2

BFI2 Dataset
HCIgrads

Homeostasis concept inventory dataset of graduate students
HCItestretest

Homeostasis concept inventory test-retest dataset
HCItest

Homeostasis concept inventory multiple-choice dataset