NEWS

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bayesqm 0.2.0 (2026-08-20)

The model changed. 0.1.0 scored the grid positions and fit a Student-t factor model through Stan. 0.2.0 models the forced Q sort as an ordered partition of the statements, computes the probability of the observed sorting event exactly, and fits it with a Gibbs sampler written in R. Stan is no longer used. Scripts written against 0.1.0 need the changes below.

Changes from 0.1.0

• fit_bayesian() fits the new model. The Stan-era arguments give migration errors that name their replacements.
• Functions keeping their names now return the new model's quantities. compute_loadings() gives bounded loadings with credible intervals, compute_zscores() scores with intervals from the aligned draws, compute_factor_array() a quota-exact array built from posterior column probabilities, and matchalign() takes and returns a whole fit.
• Removed with the score-scale model, each erroring with a pointer to its successor: run_bayes(), select_k_peak(), select_k_sivula(), compute_dominant_prob(), compute_dominant_sign(), compute_threshold_prob(), classify_membership(), compute_divergence(), critical_delta(), compute_posterior_scalars(), demo_run(), and plot_hyper(). suggest_delta() is replaced by delta_grid(), and residuals() on a fit errors because a rank likelihood has no residual scale.
• The fit object was rebuilt. The 0.1.0 slots are gone, and every table now comes from its own function.

New

• One rule behind every claim. claims() selects the reported flags, distinguishing statements, consensus statements, and pairwise stars at a posterior false-discovery level and gives the expected number of false claims.
• A two-part choice of the number of factors. fit_ladder() fits the candidate models and select_k() checks each for adequacy and for per-factor support, refusing to select when no K passes both. loo_ladder() adds PSIS-LOO as directional corroboration.
• Model checks. check_fit() runs the posterior-predictive checks and check_persons() separates sorts the model spans from shared viewpoints it does not. Every fit passes a convergence check before it returns, and extend() continues a chain draw for draw.
• The tables. compute_flags() reports flag probabilities with an explicit unclassified state, compute_qdc() judges statements against a posterior critical difference and the one-grid-column consensus region with two-level stars, and factor_characteristics() gives the per-factor summary block.
• Alignment ends in a stabilized orientation, so the delivered rotation does not inherit one draw's sampling noise.
• Two real panels ship with the package. obesity_sorts is the childhood obesity panel of Akhtar-Danesh (2023), 33 participants sorting 42 statements on a nine-column grid, and grizzly_sorts the grizzly bear reintroduction panel of Easter et al. (2025), 67 participants sorting 41 statements on an eleven-column grid.
• Plots rebuilt in one style, from plot_sorts(), which previews every participant's completed sort before any model runs, to plot_choice_k(), which draws the whole choice-of-K decision with its verdict written on the rows. plot_zscores(), plot_statement(), plot_factor_array(), plot_contrasts(), plot_flags(), plot_loading_posterior(), plot_person_check(), plot_convergence(), and plot_ppc() cover the remaining views, with ggplot2::autoplot() methods for loadings, flags, contrasts, and the array.
• rotate_factors() applies judgmental rotation to every draw, flip_factor() reverses a pole, and rename_factors() relabels every table at once.
• Data import is unchanged, and grids with any distinct printed labels are accepted as they are.
• A second vignette, the output codebook, defines every column of every reported table, and the website gains three articles, the validation checks, the decision rules, and a start-to-finish walkthrough of the obesity panel.

Dependencies

Stan is gone. rstantools, cmdstanr, rstan, GPArotation, and lpSolve are no longer used, posterior moved to Imports, and clue joined Suggests.

bayesqm 0.1.0 (2026-06-17)

First CRAN release. A Student-t factor model for Q sorts fitted through Stan, with MatchAlign post-processing, membership probabilities, and PSIS-LOO factor enumeration.