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  "Title": "Fisherian and Neymanian Methods for Detecting and Measuring\nTreatment Effect Variation",
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  "Date": "2026-02-24",
  "Authors@R": "c(\nperson(\"Peng\", \"Ding\", email = \"pengdingpku@berkeley.edu\", role = \"aut\"),\nperson(\"Avi\", \"Feller\", email = \"afeller@berkeley.edu\", role = \"aut\"),\nperson(\"Ben\", \"Fifield\", email = \"benfifield@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Luke\", \"Miratrix\", email = \"lmiratrix@g.harvard.edu\", role = \"aut\")\n)",
  "Description": "Implements methods developed by Ding, Feller, and Miratrix\n(2016) <doi:10.1111/rssb.12124> <doi:10.48550/arXiv.1412.5000>,\nand Ding, Feller, and Miratrix (2018)\n<doi:10.1080/01621459.2017.1407322>\n<doi:10.48550/arXiv.1605.06566> for testing whether there is\nunexplained variation in treatment effects across observations,\nand for characterizing the extent of the explained and\nunexplained variation in treatment effects. The package\nincludes wrapper functions implementing the proposed methods,\nas well as helper functions for analyzing and visualizing the\nresults of the test.",
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    "SKS_stat_cov_rq",
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    "WSKS.t"
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      "title": "Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation",
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        "hettx"
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