Changes in version 0.1.0                        

  - 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.

First release.

  - launch_workbench(): a seven-step Shiny app that writes reproducible
    R code.
  - select_model(): compares candidate IRT models and explains the
    recommendation.
  - interpret() and interpret_prompt(): plain-language summaries of mirt
    results.
  - tidy(), glance(), augment() and item_table() for mirt models.
  - ggplot2 graphics: gg_trace(), gg_info(), gg_wright(), gg_itemfit(),
    gg_q3(), gg_scores(), gg_empirical() and autoplot().
  - item_card() and item_cards(): item health cards with a traffic-light
    status.
  - mv_report(): a self-contained HTML report.
  - fit_rt() and sim_rt(): joint modelling of responses and response
    times with rapid-guessing flags, response time effort and l_t person
    fit.