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Changelog

Source: NEWS.md

mirtverse (development version)

  • fit_rt() gains the normative threshold rules flag_method = "nt15" and "nt20" for rapid guessing (15% and 20% of each item’s mean response time), next to "nt10", and the workbench offers all three. Following Wise and Ma (2012), the item thresholds of all three rules are now capped at 10 seconds; change the cap with the new nt_max argument (nt_max = Inf removes it). The thresholds used are returned in $thresholds.
  • New mv_dashboard() builds a read-only ‘shiny’ dashboard of your results for people who do not use R. Choose the panels (summary, items with health cards, item curves with an ability slider, information, Wright map, score distribution and conversion table, and optionally person scores, DIF and response times), add a title and logo, and run it. export_dashboard() saves it as an app.R folder ready for shinyapps.io or Posit Connect. The saved dashboard holds summaries only, never the item responses, and holds individual scores only when you add the "persons" panel.
  • export_dashboard(format = "html") saves the dashboard as one self-contained HTML file that needs no server, no R and no internet connection. The item table, item curves with the ability slider, item information and person lookup stay interactive.
  • New mv_ask() writes a complete, commented analysis script from a plain-language request such as “fit a 2PL, check DIF by gender and make a report”. Requests are understood by Claude, OpenAI GPT or a local Ollama model (set up once with mv_ask_setup()), or offline by a built-in keyword parser that asks follow-up questions. Only a column summary is ever sent; anonymize = TRUE hides column names and dry_run = TRUE shows exactly what would be sent. Scripts can be refined (mv_ask(scr, "use a 3PL instead")) and are built from an analysis plan (mv_plan()): data preparation, model fitting or selection, fit checks, DIF, scores, graphics, item cards, reports and response times. run_script() runs it, optionally after a dry run on simulated data with the same structure, and save_script() writes it to a file. profile_data() shows the column summary that is the only information shared with an AI model. The workbench now writes its code with the same templates.
  • New dif() tests every item for differential item functioning between groups in one call, with likelihood-ratio tests, adjusted p-values and expected-score effect sizes. gg_dif() plots the effects or the item curves by group, interpret() describes the results, and mv_report(dif = ) adds a DIF section to the report.
  • fit_rt() no longer fails when some persons have no item responses. mirt drops those rows from the fitted data; fit_rt() now keeps them, and their response times still inform speed.

mirtverse 0.1.0

First release.