Package: eirm 0.5
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.
Authors:
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eirm.pdf |eirm.html✨
eirm/json (API)
NEWS
# Install 'eirm' in R: |
install.packages('eirm', repos = c('https://okanbulut.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/okanbulut/eirm/issues
- VerbAggWide - Verbal Aggression Data in a Wide Format
- testdata - Fabricated Short Quiz with Explanatory Variables
Last updated 2 years agofrom:0fcc158806. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 22 2024 |
R-4.5-win | OK | Oct 22 2024 |
R-4.5-linux | OK | Oct 22 2024 |
R-4.4-win | NOTE | Oct 22 2024 |
R-4.4-mac | NOTE | Oct 22 2024 |
R-4.3-win | NOTE | Oct 22 2024 |
R-4.3-mac | NOTE | Oct 22 2024 |
Exports:%>%eirmeirmShinymarginalplotpolyreformat
Dependencies:base64encblmebootbslibcachemcellrangerclicolorspacecommonmarkcpp11crayondigestfansifarverfastmapfontawesomefsggeffectsggplot2gluegtablehmshtmltoolshttpuvinsightisobandjquerylibjsonlitelabelinglaterlatticelifecyclelme4magrittrMASSMatrixmemoisemgcvmimeminqamunsellnlmenloptrnumDerivoptimxpillarpkgconfigplyrpracmaprettyunitsprogresspromisesR6rappdirsRColorBrewerRcppRcppEigenreadxlrematchreshape2rlangsassscalesshinyshinycssloadersshinydashboardsourcetoolsstringistringrtibbleutf8vctrsviridisLitewithrxtable