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eRm (version 0.15-6)

eRm-package: extended Rasch modeling

Description

This package estimates extended Rasch models, i.e. the ordinary Rasch model for dichotomous data (RM), the linear logistic test model (LLTM), the rating scale model (RSM) and its linear extension (LRSM), the partial credit model (PCM) and its linear extension (LPCM). The parameters are estimated by conditional maximum likelihood (CML). Missing values are allowed in the data matrix. Additional features are the estimation of the person parameters, LR-Model test, item-spefific Wald test, Martin-Loef test, nonparametric Monte-Carlo tests, itemfit and personfit statistics, various ICC plots. An eRm platform is provided at http://r-forge.r-project.org/projects/erm/.

Arguments

encoding

UTF-8

cr

  • Version:
  • LRSM(X, W, mpoints = 2, groupvec = g), LPCM(X, W, mpoints = 2, groupvec = g), and as very flexible multidimensional model for repeated measurements LLRA(X, W, mpoints = 2, groups = G), mpoints specifies the number of measurement or time points, g is a vector with the group membership for each subject, ordered according to the rows of the data matrix, and G is a matrix with subject covariates (e.g., treatments), RM produces an object belonging to the classes dRm, Rm, and eRm. PCM and RSM produce objects belonging to the classes Rm and eRm, whereas results of LLTM, LRSM, LLTM and LLRA are objects of class eRm. For a detailled overview of all classes defined in the package and the functions depending on them see the package's vignette. We acknowledge Julian Gilbey for writing the plotPWmap function, Kathrin Gruber for the function plotDIF, and Thomas Rusch for LLRA, related utilities and functionality to calculate and plot item and test information. The eRm package contains functions from the packages sna, gtools and ROCR. Thanks to Carter T. Butts, Gregory R. Warnes, and Tobias Sing et al.

Sexpr

  • [stage=build]{packageDescription("eRm")$Version} Date:
  • [stage=build]{packageDescription("eRm")$Date} License:
  • [stage=build]{packageDescription("eRm")$License}

code

LLTM(X, W, mpoints = 2, groupvec = g)

Details

ll{Package: }eRm Type:

References

Fischer, G. H., and Molenaar, I. (1995). Rasch Models - Foundations, Recent Developements, and Applications. Springer. Mair, P., and Hatzinger, R. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20(9), 1-20. Mair, P., and Hatzinger, R. (2007). CML based estimation of extended Rasch models with the eRm package in R. Psychology Science, 49, 26-43.