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  "Title": "Analysis of Data from Multiple-Response Questionnaires",
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  "Authors@R": "person(given = \"Benjamin\",family = \"Mahieu\",role = c(\"aut\",\"cre\"),email = \"benjamin.mahieu@oniris-nantes.fr\")",
  "Description": "Provides a multiple-response chi-square framework for the\nanalysis of contingency tables arising from multiple-response\nquestionnaires, such as check-all-that-apply tasks, where\nresponse options are crossed with a known grouping factor. The\nframework accommodates within-block (e.g., within-subject)\ndesigns, as commonly encountered in sensory evaluation. It\ncomprises a multiple-response chi-square test of homogeneity\nwith an associated dimensionality test, a multiple-response\nCorrespondence Analysis (CA), and per-cell multiple-response\nhypergeometric tests. These methods extend their classical\ncounterparts by grounding inference in a null model that\nproperly accounts for the multiple-response nature of the data,\ntreating evaluations, rather than individual citations, as the\nexperimental units, yielding more statistically valid\nconclusions than standard contingency table analyses. Details\nmay be found in Mahieu, Schlich, Visalli, and Cardot (2021).\n<doi:10.1016/j.foodqual.2021.104256>.",
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  "Author": "Benjamin Mahieu [aut, cre]",
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