ccva 0.1.0

First release.

• Data contract as_ccva(): any dataset, columns tagged to exposure, sensitivity and adaptive capacity, with directions and outcome proxies.
• Simulator ccva_simulate() with a known latent structure (linear or nonlinear truth, optional genomic block) and bundled dataset ccva_sim.
• Component scoring: Ofori-style ordinal, continuous mean, PCA and sign-constrained penalised regression.
• Combination models: weighted index (Ofori et al. 2017, corrected normalisation), shape-constrained additive model (scam), constrained latent SEM (lavaan) with shared-error method factors, and penalised two-stage model (glmnet).
• Constraint system on predictors and components: sign, bounds, equality, fixed values and adaptive capacity as moderator.
• Diagnostics, validation, method comparison, bootstrap and weight uncertainty (with factor-score error for latent models), calibrated classification, plots for every step and an HTML report.
• Method registry ccva_register() for contributed methods.
• Framework tools: directed links between components (constrain_link()) with direct, indirect and total effects, or two-stage resolution; formative components (as_ccva(formative = )) and mean inter-item correlation in ccva_check(); concave / convex shapes (constrain_shape()); calibrated risk predictions (ccva_calibrate()); method recommendations by data availability (ccva_recommend()); assay methodology adjustment (ccva_adjust_method()); community / site aggregation (ccva_aggregate()); workflow vignette “framework”.