{ "_id": "6a214976cd65a98ecbd2c174", "Package": "cosmic", "Title": "Conditional Ordinal Stereotype Model for Incident-Level\nComparison", "Version": "0.5", "Authors@R": "person(\"Greg\", \"Ridgeway\", , \"gridge@upenn.edu\", role = c(\"aut\", \"cre\"))", "Description": "Implements the Conditional Ordinal Stereotype Model for\nIncident-Level Comparison (COSMIC), a method for analyzing\nordinal outcomes observed across multiple actors within shared\nevents. The model uses a conditional likelihood to remove\nevent-level confounding and estimate actor-specific\npropensities relative to their peers. Efficient computation is\nachieved via a dynamic programming algorithm for the\nPoisson-multinomial normalization term, enabling scalable\nestimation with Markov chain Monte Carlo. The package provides\ntools for data preparation, model fitting using Stan, and\nextraction of posterior summaries for comparative inference.\nEstimation of police officer propensity to escalate force is\nthe primary motivation for the model. For more details see\nRidgeway (2026) \"A Conditional Ordinal Stereotype Model to\nEstimate Police Officers’ Propensity to Escalate Force\"\n.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Additional_repositories": "https://stan-dev.r-universe.dev", "Config/testthat/edition": "3", "VignetteBuilder": "knitr", "Repository": "https://gregridgeway.r-universe.dev", "Date/Publication": "2026-04-30 01:02:08 UTC", "RemoteUrl": "https://github.com/gregridgeway/cosmic", "RemoteRef": "HEAD", "RemoteSha": "5b6ef2e7e1f8b951f24c95031a9ef2ceb5fbc652", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-04 09:43:05 UTC", "User": "root" }, "Author": "Greg Ridgeway [aut, cre]", "Maintainer": "Greg Ridgeway ", "MD5sum": "4d46f02636b79b7ad3c7b783b6e28d4e", "_user": "gregridgeway", "_type": "src", "_file": "cosmic_0.5.tar.gz", "_fileid": "8e693671b901edbf931779667c0722a8820017bc824264eaf77336c0fe148c5b", "_filesize": 1401286, 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