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  "Maintainer": "Dylan Molenaar <d.molenaar@uva.nl>",
  "Description": "In Latent Space Item Response Models, subjects and items\nare embedded in a multidimensional Euclidean latent space. As\nsuch, interactions among persons, items, and person-item\ncombinations can be revealed that are unmodelled in more\nconventional item response theory models. This package\nimplements the methods from Molenaar & Jeon (in press) and can\nbe used to fit Latent Space Item Response Models to data using\njoint maximum likelihood estimation. The package can handle\nbinary data, ordinal data, and data with mixed scales. The\npackage incorporates facilities for data simulation, rotation\nof the latent space, and K-fold cross-validation to select the\nnumber of dimensions of the latent space.",
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      "title": "Fitting Latent Space Item Response Models using Joint Maximum Likelihood Estimation",
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