eirm-package: Profile Analysis of Multivariate Data in R
In okanbulut/eirm: Explanatory Item Response Modeling for Dichotomous and Polytomous Items
eirm-package R Documentation
Profile Analysis of Multivariate Data in R
Description
The package eirm provides a set of tools to analyze and visualize
dichotomous and polytomous item responses using the explanatory item
response modeling (EIRM). The generalized linear mixed modeling (GLMM)
framework is used for examining the impact of item-related and person-related
variables on responses. The items are repeated measures that are nested underpersons.
The model details can be found at de Boeck and Wilson's (2004) Explanatory Item Response Models -
A Generalized Linear and Nonlinear Approach <DOI: 10.1007/978-1-4757-3990-9>.
Author(s)
Okan Bulut bulut@ualberta.ca
References
De Boeck, P., & Wilson, M. (2004). Explanatory item response models: A generalized linear
and nonlinear approach. New York: Springer-Verlag.
okanbulut/eirm documentation built on March 5, 2023, 6:22 a.m.
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| eirm-package | R Documentation |
Profile Analysis of Multivariate Data in R
Description
The package eirm provides a set of tools to analyze and visualize dichotomous and polytomous item responses using the explanatory item response modeling (EIRM). The generalized linear mixed modeling (GLMM) framework is used for examining the impact of item-related and person-related variables on responses. The items are repeated measures that are nested underpersons. The model details can be found at de Boeck and Wilson's (2004) Explanatory Item Response Models - A Generalized Linear and Nonlinear Approach <DOI: 10.1007/978-1-4757-3990-9>.
Author(s)
Okan Bulut bulut@ualberta.ca
References
De Boeck, P., & Wilson, M. (2004). Explanatory item response models: A generalized linear and nonlinear approach. New York: Springer-Verlag.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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