PACER 3.2.0

PACER 3.2.0 — Nexus

Six cognitive diagnostic models on one engine. This release adds the three classic additive CDMs — A-CDM, LLM and R-RUM — alongside G-DINA, DINA and DINO, in calibration, in the Skill Profiler, and from Claude Desktop. Estimates were verified against the GDINA R package.

What's new

A-CDM, LLM and R-RUM

• The additive models of de la Torre (2011): G-DINA with the interaction terms removed, so each required skill adds a fixed main effect on the probability scale (A-CDM, identity link), the log-odds scale (LLM, the linear logistic model, logit link) or the log scale (R-RUM, log link). An item requiring k skills has k + 1 parameters instead of 2^k.
• Fitted by the same multi-start EM engine as G-DINA with a Newton (Fisher-scoring) M-step. One-skill items use the closed form.
• Every item still reports pattern probabilities, δ, guess, slip, IDI, the monotonicity check, and the fit indices (deviance, parameters, AIC, BIC, CAIC, AICc, SABIC), so all six models can be compared on the same data.

A model chooser that explains the link

• The Model option is now a chooser in three families — Saturated (G-DINA), Conjunctive / disjunctive (DINA, DINO), Additive (A-CDM, LLM, R-RUM) — with a one-line description of the selected model.
• For G-DINA, DINA and DINO the Link Function stays a reporting scale for δ. For the additive models it is part of the model: the selector locks and says fixed by the model.
• The item table shows the model and its link; the item plot charts P(correct) by attribute pattern for every model.

Enforce monotonicity

• New Estimation Options checkbox (off by default; the R package's mono.constraint) that constrains every main effect of an additive model to be non-negative, so P(correct) never falls when a skill is mastered. Other models keep the monotonicity check.

Skill Profiler

• Profiles examinees under all six models. The pattern-level parameter file gains a model column (G-DINA when absent) and the profiler locks its model to the loaded calibration or to the file.
• Unknown model names are reported instead of silently becoming DINA.

Claude Desktop (MCP) and the AI Advisor

• calibrate_cdm accepts ACDM, LLM and RRUM plus mono_constraint, rejects a link that conflicts with an additive model, and writes the model column; score_cdm reads it back and locks to that model. MCP server 0.4.0.
• The AI Advisor's knowledge base covers the additive models, the two roles of the link function, the Newton M-step and the monotonicity constraint.

Learn it

• CDM Calibration and Skill Profiler guided tours describe the six models in all eight languages.
• PACER University's CDM module adds Additive Models: When the Link Is the Model with a six-model fit comparison.
• The technical reference documents the additive models, their design matrix and the constrained Newton M-step.

Fixes

• /api/cdm/calibrate and /api/cdm/score now return a clear 400 error for an unknown method or link name instead of silently using DINA and the identity link.

Verification

On a 10-item, 3-skill, 1,000-examinee dataset, PACER and GDINA 2.13.1 agree on deviance to within 0.01 for A-CDM, LLM and R-RUM (and to 0.02 with the monotonicity constraint); pattern probabilities agree to three decimals. G-DINA, DINA and DINO results are unchanged from 3.1.0.

Upgrading

• Desktop users: after installing, open Settings → Connect to Claude Desktop again (the config path includes the version number), then restart Claude Desktop.
• Pattern-level parameter files exported by 3.1.0 (no model column) still import and score as G-DINA.

Downloads: PACERSetup.exe (Windows) · PACER.dmg (macOS, Apple Silicon and Intel) · web app at paceronline.com

PACER 3.1.0: Nexus

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

PACER 3.0.0 Nexus

Nexus — PACER is now callable from Claude Desktop over MCP: the full engine (calibration, scoring, DIF, equating, ATA, CDM, latent regression, plausible values) driven by chat. After updating, open Settings → Connect to Claude Desktop to re-link. See the changelog for details.

PACER 2.0.2

Updated with new expiry date to 12/31/26 and adding Mac Universal DMG

PACER 2.0.1

Explanatory IRT model now has person ID drop down selector

PACER Discover 2.0.0

V.2.0.0

Initial Commit