eirm: Explanatory Item Response Modeling for Dichotomous and Polytomous Items

Analysis of dichotomous and polytomous response data using the explanatory item response modeling framework, as described in Bulut, Gorgun, & Yildirim-Erbasli (2021) <doi:10.3390/psych3030023>, Stanke & Bulut (2019) <doi:10.21449/ijate.515085>, and De Boeck & Wilson (2004) <doi:10.1007/978-1-4757-3990-9>. Generalized linear mixed modeling is used for estimating the effects of item-related and person-related variables on dichotomous and polytomous item responses.

Version: 0.5
Depends: lme4, blme, reshape2, optimx
Imports: magrittr, shiny, shinydashboard, shinycssloaders, readxl, ggeffects, ggplot2
Suggests: knitr, rmarkdown
Published: 2021-10-25
Author: Okan Bulut ORCID iD [aut, cre]
Maintainer: Okan Bulut <bulut at ualberta.ca>
License: GPL (≥ 3)
URL: https://github.com/okanbulut/eirm
NeedsCompilation: no
Citation: eirm citation info
Materials: NEWS
CRAN checks: eirm results

Documentation:

Reference manual: eirm.pdf
Vignettes: Using eirm for estimating explanatory IRT models

Downloads:

Package source: eirm_0.5.tar.gz
Windows binaries: r-devel: eirm_0.5.zip, r-release: eirm_0.5.zip, r-oldrel: eirm_0.5.zip
macOS binaries: r-release (arm64): eirm_0.5.tgz, r-release (x86_64): eirm_0.5.tgz, r-oldrel: eirm_0.5.tgz
Old sources: eirm archive

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