R package 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).

References in zbMATH (referenced in 24 articles , 1 standard article )

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  1. Paul-Christian Burkner: Bayesian Item Response Modeling in R with brms and Stan (2021) not zbMATH
  2. Müller, Marianne: Item fit statistics for Rasch analysis: can we trust them? (2020)
  3. Christine Hohensinn: pcIRT: An R Package for Polytomous and Continuous Rasch Models (2018) not zbMATH
  4. Liu, Xiang; Han, Zhuangzhuang; Johnson, Matthew S.: The UMP exact test and the confidence interval for person parameters in IRT models (2018)
  5. Mair, Patrick: Modern psychometrics with R (2018)
  6. Víctor Cervantes: DFIT: An R Package for Raju’s Differential Functioning of Items and Tests Framework (2017) not zbMATH
  7. Bolsinova, Maria; Maris, Gunter; Hoijtink, Herbert: Unmixing Rasch scales: how to score an educational test (2016)
  8. Jorge Tendeiro and Rob Meijer and A. Niessen: PerFit: An R Package for Person-Fit Analysis in IRT (2016) not zbMATH
  9. Strobl, Carolin; Kopf, Julia; Zeileis, Achim: Rasch trees: a new method for detecting differential item functioning in the Rasch model (2015)
  10. Tutz, Gerhard; Schauberger, Gunther: A penalty approach to differential item functioning in Rasch models (2015)
  11. Wermuth, Nanny; Marchetti, Giovanni M.: Star graphs induce tetrad correlations: for Gaussian as well as for binary variables (2014)
  12. Christensen, Karl Bang: Conditional maximum likelihood estimation in polytomous Rasch models using SAS (2013)
  13. Bacci, Silvia: Longitudinal data: different approaches in the context of item-response theory models (2012)
  14. Hannah Frick; Carolin Strobl; Friedrich Leisch; Achim Zeileis: Flexible Rasch Mixture Models with Package psychomix (2012) not zbMATH
  15. R. Chalmers: mirt: A Multidimensional Item Response Theory Package for the R Environment (2012) not zbMATH
  16. Paul De Boeck; Marjan Bakker; Robert Zwitser; Michel Nivard; Abe Hofman; Francis Tuerlinckx; Ivailo Partchev: The Estimation of Item Response Models with the lmer Function from the lme4 Package in R (2011) not zbMATH
  17. Seung Choi; Laura Gibbons; Paul Crane: lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations (2011) not zbMATH
  18. Jonathan Weeks: plink: An R Package for Linking Mixed-Format Tests Using IRT-Based Methods (2010) not zbMATH
  19. Yanyan Sheng: Bayesian Estimation of MIRT Models with General and Specific Latent Traits in MATLAB (2010) not zbMATH
  20. Carolyn Anderson; Zhushan Li; Jeroen Vermunt: Estimation of Models in a Rasch Family for Polytomous Items and Multiple Latent Variables (2007) not zbMATH

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