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PACER 3.1.0: Nexus

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@hdoran hdoran released this 08 Oct 12:44
V.3.1.0
6c6b6c3

PACER 3.1.0 — Nexus

G-DINA arrives. Every combination of an item's required skills now gets its own success probability — DINA and DINO become special cases of one general cognitive diagnostic engine, in calibration, in the Skill Profiler, and from Claude Desktop.

Downloads: PACERSetup.exe (Windows 10/11, x64) · PACER-3.1.0.dmg (macOS, Apple Silicon and Intel). The web app at paceronline.com is updated too.

What's new

G-DINA calibration

  • The saturated generalized DINA model (de la Torre, 2011). For an item requiring k skills, PACER estimates P(correct) for each of its 2^k attribute patterns (00, 10, 01, 11, …) and reports the equivalent δ coefficients — intercept, main effects, interactions — under an identity, logit, or log link.
  • Choose G-DINA, DINA, or DINO with one click. Each item row expands to its pattern view; a new Parameters by Attribute Pattern table lists every item × pattern with search, paging, and CSV export.
  • Results match the R GDINA package on the same data (deviance, pattern probabilities, and δ agree to the fourth decimal).

Model fit and monotonicity

  • Every CDM now reports deviance, number of free parameters, and AIC, BIC, CAIC, AICc, and SABIC — so DINA, DINO, and G-DINA can be compared on the same data.
  • A monotonicity check flags items whose success probability falls when an additional required skill is mastered (usually a mis-specified Q-matrix row).
  • DINA and DINO are now estimated by the same multi-start EM engine as G-DINA (structured starting values with a fixed seed), which also lets them escape poor local optima. New Estimation Options accordion: link, starting values, seed, monotonicity check. Defaults are tighter: tolerance 0.0001, 500 iterations.

Skill Profiler, G-DINA aware

  • Scores with whichever model the items were calibrated under. The model toggle is set from the loaded calibration or the uploaded parameter file and locked, so parameters and model can no longer disagree.
  • New pattern-level parameter file (item, pattern, p_success), exported by calibration and read back by the profiler, carries G-DINA parameters between sessions. Guess/slip files still work for DINA/DINO.
  • Every run returns the posterior probability of mastering each skill. EAP shows these in the table and CSV; the examinee diagnostic lists each item's required-skill pattern, the model's P(correct), and whether the response was expected.

Claude Desktop and the AI Advisor

  • calibrate_cdm accepts method: GDINA plus link, n_starts, seed, and mono_check, and writes the pattern-level file; score_cdm reads it back, scores with the calibration's model, and reports mastery probabilities. Tool defaults equal the UI defaults.
  • The local AI Advisor's knowledge base now covers G-DINA (model, δ, fit statistics, sidebar options) and the Claude Desktop integration itself.

Learn it

  • CDM Calibration guided tour expanded to 15 steps covering the new model, fit cards, and pattern tables; Skill Profiler tour updated — both in all eight languages.
  • PACER University's CDM module starts with DINA, then introduces G-DINA with an interactive pattern explorer and a real DINA-vs-G-DINA fit comparison.
  • Technical reference documents the model, closed-form EM, δ, and fit statistics; the Template Library includes the pattern-level parameter file.

Fixes

  • IRT Calibration: item anchors were silently ignored when Estimate population μ and σ was on and a polytomous column preceded the anchored item. Anchors are now pinned exactly on every estimation path, including multigroup.
  • Skill Profiler: blank responses were scored as wrong; a guess or slip of exactly 0 was replaced by 0.2; uploaded item names were lost; EAP mastery was rounded to 0/1. All corrected.

Upgrading

  • Claude Desktop users: after installing, open Settings → Connect to Claude Desktop again and restart Claude Desktop — the connection is pinned to the installed version.
  • Saved DINA/DINO calibrations and parameter files load unchanged. Because DINA/DINO now use the multi-start engine, re-running an old calibration may give slightly different (better-fitting) estimates.
  • Windows SmartScreen may warn on first run: More info → Run anyway.

Full changelog: https://www.paceronline.com/changelog.html

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