{
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  "Package": "cata",
  "Type": "Package",
  "Title": "Analysis of Check-All-that-Apply (CATA) Data",
  "Version": "0.1.2.0",
  "Date": "2026-07-31",
  "Author": "J.C. Castura [aut, cre, ctb] (ORCID:\n<https://orcid.org/0000-0002-1640-833X>)",
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  "Maintainer": "J.C. Castura <jcastura@compusense.com>",
  "Description": "Package contains functions for analyzing\ncheck-all-that-apply (CATA) data from consumer and sensory\ntests. Cochran's Q test, McNemar's test, and Penalty-Lift\nanalysis are provided; for details, see Meyners, Castura & Carr\n(2013) <doi:10.1016/j.foodqual.2013.06.010>. Cluster analysis\ncan be performed using b-cluster analysis, then evaluated using\nvarious measures; for details, see Castura, Meyners, Varela &\nNæs (2022) <doi:10.1016/j.foodqual.2022.104564>. Consumers can\nalso be clustered on their product-related hedonic responses;\nsee Castura, Meyners, Pohjanheimo, Varela & Næs (2023)\n<doi:10.1111/joss.12860>. Permutation tests based on the\nL1-norm methods are provided; for details, see Chaya, Castura &\nGreenacre (2025) <doi:10.1016/j.foodqual.2025.105639>.",
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    "rv.coef",
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    "toTallMatrix",
    "toWideMatrix"
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      "title": "Consumer CATA data set: bread",
      "object": "bread",
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      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
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      "title": "Consumer CATA data set: squashes",
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      "table": false,
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      "title": "Adjusted Rand index",
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      ]
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      "page": "barray",
      "title": "Convert CATA binary data to CATA differences array",
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    },
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    },
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      ]
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    {
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      "title": "b-cluster analysis by hierarchical agglomerative strategy",
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    },
    {
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      ]
    },
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      ]
    },
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    },
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      ]
    },
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      ]
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    },
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      "title": "Permutation tests for CATA data",
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