{
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  "Title": "Hierarchical Signal Detection Theory Models for Unconscious\nProcessing",
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  "Authors@R": "c(\nperson(\"Ricardo\", \"Rey-Sáez\",\nemail   = \"ricardoreysaez95@gmail.com\",\nrole    = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-6739-2035\")),\nperson(\"Francisco\", \"Garre-Frutos\",\nemail   = \"fgfrutos@gmail.com\",\nrole    = \"aut\",\ncomment = c(ORCID = \"0000-0001-9810-186X\")),\nperson(\"Alicia\", \"Franco-Martínez\",\nemail   = \"aliciafranco96@gmail.com\",\nrole    = \"aut\",\ncomment = c(ORCID = \"0000-0002-9710-1240\")),\nperson(\"Miguel\", \"Vadillo\",\nemail   = \"mgl.vadillo@gmail.com\",\nrole    = \"aut\",\ncomment = c(ORCID = \"0000-0001-8421-816X\")))",
  "Description": "Fits hierarchical signal detection theory (SDT) models to\npaired direct and indirect measures, the design used to test\nfor unconscious processing. Continuous indirect measures\n(typically response times) are dichotomized with the\nwithin-subject median split of Meyen et al. (2022)\n<doi:10.1037/xge0001065> so that both tasks are placed on a\ncommon sensitivity scale. The package estimates a binomial\nprobit mixed model in which the two sensitivities are\ncorrelated random effects, and tests the three hypotheses of\ninterest: the group-level difference between sensitivities,\ntheir latent correlation, and the latent regression of the\nindirect on the direct measure, whose intercept is the test for\nunconscious processing. Frequentist estimation uses 'lme4'.",
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  "Author": "Ricardo Rey-Sáez [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-6739-2035>), Francisco\nGarre-Frutos [aut] (ORCID:\n<https://orcid.org/0000-0001-9810-186X>), Alicia\nFranco-Martínez [aut] (ORCID:\n<https://orcid.org/0000-0002-9710-1240>), Miguel Vadillo [aut]\n(ORCID: <https://orcid.org/0000-0001-8421-816X>)",
  "Maintainer": "Ricardo Rey-Sáez <ricardoreysaez95@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
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      "title": "Fit a hierarchical signal detection theory model",
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      "title": "Diagnostic and analytical plots for hierarchical SDT models",
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      "title": "Signal detection measures for each subject",
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        "What is uSDT for?",
        "The data",
        "Preparing the data",
        "Condition coding: deviation vs treatment",
        "How the median split works",
        "Inspecting the prepared data",
        "Fitting the model",
        "Understanding fixed and random effects",
        "Testing unconscious processing: The three hypotheses",
        "H1: Group-level sensitivity difference ($\\Delta d'$)",
        "H2: Latent correlation between tasks ($\\rho$)",
        "H3: Latent regression (Indirect $d'$ on Direct $d'$)",
        "Reliability of individual differences",
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        "References"
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