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easyRasch2  

Psychometric Analysis with Rasch Measurement Theory
View on CRAN: Click here


Download and install easyRasch2 package within the R console
Install from CRAN:
install.packages("easyRasch2")

Install from Github:
library("remotes")
install_github("cran/easyRasch2")

Install by package version:
library("remotes")
install_version("easyRasch2", "0.8.0")



Attach the package and use:
library("easyRasch2")
Maintained by
Magnus Johansson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-08
Latest Update: 2026-06-08
Description:
Streamlines reproducible Rasch measurement theory analyses for ordinal item-response data, combining estimation routines from 'eRm', 'psychotools', 'mirt', 'iarm', and 'lavaan' with consistent diagnostic, plotting, and reporting layers. Covers the four basic psychometric criteria summarised by Christensen et al. (2021) <doi:10.1111/sms.13908> – unidimensionality, local independence, ordered response category thresholds, and invariance across subgroups – together with item fit, targeting, reliability, category functioning, and descriptive item-response plots. A distinguishing feature is the use of simulation-based critical values to replace rule-of-thumb cutoffs for conditional infit mean-square, Yen's Q3 local-dependence statistic, the largest residual-PCA eigenvalue, and ordinal CFA fit indices. Outputs are knitr::kable() tables and 'ggplot2' figures suitable for direct inclusion in 'Quarto' and 'R Markdown' reports.
How to cite:
Magnus Johansson (2026). easyRasch2: Psychometric Analysis with Rasch Measurement Theory. R package version 0.8.0, https://cran.r-project.org/web/packages/easyRasch2. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-08-04 20:00), 0.8.0 (2026-06-08 19:50), 1.0.0 (2026-07-05 17:50), 1.1.0 (2026-07-14 20:10)
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Complete documentation for easyRasch2
Functions, R codes and Examples using the easyRasch2 R package
Full easyRasch2 package functions and examples
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