eRm: Extended Rasch Modeling eRm fits Rasch models (RM), linear logistic test models (LLTM), rating scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), and linear partial credit models (LPCM). Missing values are allowed in the data matrix. Additional features are the ML estimation of the person parameters, Andersen’s LR-test, item-specific Wald test, Martin-Loef-Test, nonparametric Monte-Carlo Tests, itemfit and personfit statistics including infit and outfit measures, various ICC and related plots, automated stepwise item elimination, simulation module for various binary data matrices. An eRm platform is provided at R-forge (see URL).
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References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Víctor Cervantes: DFIT: An R Package for Raju’s Differential Functioning of Items and Tests Framework (2017)
- Bolsinova, Maria; Maris, Gunter; Hoijtink, Herbert: Unmixing Rasch scales: how to score an educational test (2016)
- Strobl, Carolin; Kopf, Julia; Zeileis, Achim: Rasch trees: a new method for detecting differential item functioning in the Rasch model (2015)
- Tutz, Gerhard; Schauberger, Gunther: A penalty approach to differential item functioning in Rasch models (2015)
- Wermuth, Nanny; Marchetti, Giovanni M.: Star graphs induce tetrad correlations: for Gaussian as well as for binary variables (2014)
- Christensen, Karl Bang: Conditional maximum likelihood estimation in polytomous Rasch models using SAS (2013)