https://epistemic-analytics.r-universe.devRecent package updates in epistemic-analyticsR-universehttps://github.com/epistemic-analytics.pnghttps://epistemic-analytics.r-universe.devWed, 14 Oct 2026 11:11:27 GMTcody.marquart@wisc.edu (Cody L Marquart)ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models. Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).https://github.com/r-universe/epistemic-analytics/actions/runs/38619125382Wed, 14 Oct 2026 11:11:27 GMTrENA0.4.14successhttps://epistemic-analytics.r-universe.devhttps://gitlab.com/epistemic-analytics/qe-packages/renacody.marquart@wisc.edu (Cody L Marquart)Rho is used to test the generalization of inter rater reliability (IRR) statistics. Calculating rho starts by generating a large number of simulated, fully-coded data sets: a sizable collection of hypothetical populations, all of which have a kappa value below a given threshold -- which indicates unacceptable agreement. Then kappa is calculated on a sample from each of those sets in the collection to see if it is equal to or higher than the kappa in then real sample. If less than five percent of the distribution of samples from the simulated data sets is greater than actual observed kappa, the null hypothesis is rejected and one can conclude that if the two raters had coded the rest of the data, we would have acceptable agreement (kappa above the threshold).https://github.com/r-universe/epistemic-analytics/actions/runs/35992285622Mon, 20 Oct 2025 13:12:55 GMTrhoR1.3.1successhttps://epistemic-analytics.r-universe.devhttps://gitlab.com/epistemic-analytics/qe-packages/rhorcody.marquart@wisc.edu (Cody L Marquart)A set of techniques that can be used to develop, validate, and implement automated classifiers. A powerful tool for transforming raw data into meaningful information, 'ncodeR' (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is designed specifically for working with big data: large document collections, logfiles, and other text data.https://github.com/r-universe/epistemic-analytics/actions/runs/34951375428Fri, 21 May 2021 20:08:29 GMTncodeR0.2.1.1successhttps://epistemic-analytics.r-universe.devhttps://gitlab.com/epistemic-analytics/qe-packages/ncoder