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  "Title": "Generate Postestimation Quantities for Bayesian MCMC Estimation",
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  "Date": "2025-08-13",
  "Authors@R": "c(person(\"Johannes\",\n\"Karreth\",\nemail = \"jkarreth@ursinus.edu\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0003-4586-7153\")),\nperson(\"Shana\",\n\"Scogin\",\nemail = \"shanarscogin@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-7801-853X\")),\nperson(\"Rob\",\n\"Williams\",\nemail = \"jayrobwilliams@gmail.com\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-9259-3883\")),\nperson(\"Andreas\",\n\"Beger\",\nemail = \"adbeger@gmail.com\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0003-1883-3169\")),\nperson(\"Myunghee\",\n\"Lee\",\nrole = c(\"ctb\")),\nperson(\"Neil\",\n\"Williams\",\nrole = c(\"ctb\")))",
  "Description": "An implementation of functions to generate and plot\npostestimation quantities after estimating Bayesian regression\nmodels using Markov chain Monte Carlo (MCMC). Functionality\nincludes the estimation of the Precision-Recall curves (see\nBeger, 2016 <doi:10.2139/ssrn.2765419>), the implementation of\nthe observed values method of calculating predicted\nprobabilities by Hanmer and Kalkan (2013)\n<doi:10.1111/j.1540-5907.2012.00602.x>, the implementation of\nthe average value method of calculating predicted probabilities\n(see King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>),\nand the generation and plotting of first differences to\nsummarize typical effects across covariates (see Long 1997,\nISBN:9780803973749; King, Tomz, and Wittenberg, 2000\n<doi:10.2307/2669316>). This package can be used with MCMC\noutput generated by any Bayesian estimation tool including\n'JAGS', 'BUGS', 'MCMCpack', and 'Stan'.",
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      "buildurl": "https://github.com/r-universe/shanascogin/actions/runs/25721428701"
    }
  ]
}