NEWS.md

In NPCDTools: The Nonparametric Classification Methods for Cognitive Diagnosis

NPCDTools 1.2.0

• Renamed the NPC() output component alpha.est to att.est for consistency with GNPC(). This is a breaking change: code using NPC(...)$alpha.est must now use NPC(...)$att.est.

NPCDTools 1.1.0

New Functions

• distractor.check(): Detects implausible and improper distractors in a Q-matrix for multiple-choice items (Chiu, Köhn, & Wang, in press).
• Q.implausible(): Generates a Q-matrix containing implausible MC item distractors from a proper and plausible Q-matrix.
• Q.improper(): Generates a Q-matrix containing improper MC item distractors from a proper and plausible Q-matrix.
• plot.GNPC(): S3 plot method for GNPC objects, providing convergence tracking visualization for individual examinees.
• run_gnpc_app(): Launches an interactive Shiny application demonstrating NPC, GNPC, and G-DINA workflows.

New Dataset

• Q_Ozaki: A Q-matrix for 30 multiple-choice items measuring 5 attributes from Ozaki (2015), including coded distractors.

Improvements

• Added S3 print methods for GNPC, NPC, QR, Q.completeness, and distractor.check objects, providing structured and informative summaries.
• Added convergence tracking option in GNPC() via the track.convergence argument.
• Improved input validation across functions via internal CheckInput().
• Consolidated internal pattern generation for consistency across all functions.

Dependency Changes

• Removed dependency on NPCD. The TSQE() function now uses the package's own QR() function for Q-matrix refinement instead of NPCD::Qrefine().
• Removed dependency on SimDesign.

NPCDTools 1.0

• Initial CRAN release (2024-09-23).
• Core nonparametric classification methods: NPC() and GNPC().
• Q-matrix tools: Q.completeness(), Q.generate(), QR(), TSQE(), bestQperm().
• Evaluation metrics: AAR(), PAR(), RR(), correction.rate(), retention.rate().

NPCDTools documentation built on Sept. 1, 2026, 1:08 a.m.