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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  [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:
Downloads:
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