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  "Title": "Functions for Applying the T^2-Test for Equivalence",
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  "Author": "Thomas Hoffelder",
  "Maintainer": "Thomas Hoffelder\n<thomas.hoffelder@boehringer-ingelheim.com>",
  "Description": "Contains functions for applying the T^2-test for\nequivalence. The T^2-test for equivalence is a multivariate\ntwo-sample equivalence test. Distance measure of the test is\nthe Mahalanobis distance. For multivariate normally distributed\ndata the T^2-test for equivalence is exact and UMPI. The\nfunction T2EQ() implements the T^2-test for equivalence\naccording to Wellek (2010) <DOI:10.1201/ebk1439808184>. The\nfunction T2EQ.dissolution.profiles.hoffelder() implements a\nvariant of the T^2-test for equivalence according to Hoffelder\n(2016) <http://www.ecv.de/suse_item.php?suseId=Z|pi|8430> for\nthe equivalence comparison of highly variable dissolution\nprofiles.",
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      "title": "Functions for Applying the T^2-Test for Equivalence",
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        "multivariate statistics",
        "equivalence",
        "two-sample design",
        "Mahalanobis distance",
        "Hotelling's T^2",
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        "multivariate normal distribution"
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      "title": "Example dataset from Hoffelder (2016)",
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        "ex_data_pharmind"
      ]
    },
    {
      "page": "T2EQ",
      "title": "Function for applying the T^2-test for equivalence",
      "concept": [
        "multivariate statistics",
        "equivalence",
        "two-sample design",
        "Mahalanobis distance",
        "Hotelling's T^2",
        "multivariate normal distribution"
      ],
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      "title": "The T^2-test for equivalence for dissolution data",
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        "equivalence",
        "two-sample design",
        "Mahalanobis distance",
        "Hotelling's T^2",
        "dissolution profiles"
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