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@ -20162,3 +20162,35 @@ multi-faceted Rasch model, nominal item response model, structured latent
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class model, mixture distribution IRT models, and located latent class models.
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class model, mixture distribution IRT models, and located latent class models.
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Latent regression models and plausible value imputation are also supported.")
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Latent regression models and plausible value imputation are also supported.")
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(license license:gpl2+)))
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(license license:gpl2+)))
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(define-public r-erm
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(package
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(name "r-erm")
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(version "1.0-0")
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(source
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(origin
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(method url-fetch)
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(uri (cran-uri "eRm" version))
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(sha256
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(base32
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"11p8j61arq1ih2qi33wf0442vcdbp3zvknzm5aknsifwl4mbzzly"))))
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(properties `((upstream-name . "eRm")))
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(build-system r-build-system)
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(propagated-inputs
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`(("r-lattice" ,r-lattice)
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("r-mass" ,r-mass)
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("r-matrix" ,r-matrix)))
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(native-inputs `(("gfortran" ,gfortran)))
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(home-page "https://cran.r-project.org/package=eRm")
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(synopsis "Extended Rasch modeling")
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(description
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"This package provides tools to fit @dfn{Rasch models} (RM), @dfn{linear
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logistic test models} (LLTM), @dfn{rating scale model} (RSM), @dfn{linear
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rating scale models} (LRSM), @dfn{partial credit models} (PCM), and
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@dfn{linear partial credit models} (LPCM). Missing values are allowed in the
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data matrix. Additional features are the ML estimation of the person
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parameters, Andersen's LR-test, item-specific Wald test, Martin-Loef-Test,
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nonparametric Monte-Carlo Tests, itemfit and personfit statistics including
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infit and outfit measures, ICC and other plots, automated stepwise item
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elimination, and a simulation module for various binary data matrices.")
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(license license:gpl3)))
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