{ "_id": "6a153725acfb0bcc41d4f94c", "Type": "Package", "Package": "tidylo", "Title": "Weighted Tidy Log Odds Ratio", "Version": "0.2.0.9000", "Authors@R": "c(\nperson(\"Tyler\", \"Schnoebelen\", , \"tjs1976@gmail.com\", role = \"aut\"),\nperson(\"Julia\", \"Silge\", , \"julia.silge@gmail.com\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-3671-836X\")),\nperson(\"Alex\", \"Hayes\", , \"alexpghayes@gmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-4985-5160\"))\n)", "Description": "How can we measure how the usage or frequency of some\nfeature, such as words, differs across some group or set, such\nas documents? One option is to use the log odds ratio, but the\nlog odds ratio alone does not account for sampling variability;\nwe haven't counted every feature the same number of times so\nhow do we know which differences are meaningful? Enter the\nweighted log odds, which 'tidylo' provides an implementation\nfor, using tidy data principles. In particular, here we use the\nmethod outlined in Monroe, Colaresi, and Quinn (2008)\n to weight the log odds ratio by a\nprior. By default, the prior is estimated from the data itself,\nan empirical Bayes approach, but an uninformative prior is also\navailable.", "License": "MIT + file LICENSE", "URL": "https://juliasilge.github.io/tidylo/,\nhttps://github.com/juliasilge/tidylo", "BugReports": "https://github.com/juliasilge/tidylo/issues", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.1.2", "Repository": "https://juliasilge.r-universe.dev", "Date/Publication": "2022-03-22 14:56:26 UTC", "RemoteUrl": "https://github.com/juliasilge/tidylo", "RemoteRef": "HEAD", "RemoteSha": "5b8d9b0dc9edf48873c6db379e62566905e75f5d", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-26 05:58:15 UTC", "User": "root" }, "Author": "Tyler Schnoebelen [aut],\nJulia Silge [aut, cre, cph] (ORCID:\n),\nAlex Hayes [aut] (ORCID: )", "Maintainer": "Julia Silge ", "MD5sum": "b082765e8ad9e5bdf667039c6fc942c0", "_user": "juliasilge", "_type": "src", 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