Changelog

Source: NEWS.md

PTSDdiag 0.2.1

Improvements

• optimize_combinations(), optimize_combinations_clusters(), holdout_validation(), and cross_validation() now return plain data frames by default. Set DT = TRUE for interactive DT widgets (previous default behaviour).
• Combination identity (combination_id and rank columns) is now tracked through the full pipeline: optimization summaries, write_combinations() / read_combinations() JSON files, and cross-validation combination summaries.
• Progress reporting via the cli package: fold-level progress bars in cross_validation() and informational messages in holdout_validation() and the optimization functions.
• cross_validation() supports parallel fold processing via future.apply when available. Set up with future::plan(future::multisession) before calling.

Deprecations

• analyze_best_six_symptoms_four_required() and analyze_best_six_symptoms_four_required_clusters() are soft-deprecated in

  favour of optimize_combinations() and optimize_combinations_clusters().

Documentation

• Updated vignettes to use the generalized API (optimize_combinations() and optimize_combinations_clusters()) instead of legacy wrappers.

PTSDdiag 0.2.0

• New generalized optimization functions optimize_combinations() and optimize_combinations_clusters() that allow configurable number of symptoms per combination (n_symptoms), required threshold (n_required), number of top results (n_top), and custom cluster definitions (clusters).
• New apply_symptom_combinations() function for external validation: apply pre-derived combinations to a new dataset and compare against DSM-5 baseline.
• New write_combinations() and read_combinations() functions for exporting and importing optimized symptom combinations as human-readable JSON files, enabling collaboration across research groups without sharing raw data.
• Original functions analyze_best_six_symptoms_four_required() and analyze_best_six_symptoms_four_required_clusters() are preserved as backward-compatible wrappers with PCL-5 defaults.
• holdout_validation() and cross_validation() now accept n_symptoms, n_required, and n_top parameters.
• Internal refactoring: shared validation and diagnosis logic consolidated into reusable internal helpers.

PTSDdiag 0.1.0

CRAN release: 2026-02-13

• Initial CRAN submission.
• Core analysis functions for identifying optimal 6-symptom PTSD diagnostic combinations using PCL-5 data.
• Hierarchical (cluster-based) and non-hierarchical analysis approaches.
• DSM-5 diagnostic criteria implementation (binarized and non-binarized).
• Diagnostic accuracy metrics: sensitivity, specificity, PPV, NPV.
• Holdout and k-fold cross-validation methods for model evaluation.
• Simulated PCL-5 dataset with 5,000 observations for demonstration.