Package index
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fit_bayesian() - Fit the exact partition-likelihood model to forced Q sorts
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extend() - Continue sampling a fitted chain
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matchalign() - MatchAlign post-processing for partition-model draws
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delta_grid() - Grid width on the z scale
The tables
The familiar Q outputs as posterior summaries, and the one false-discovery rule behind every claim.
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compute_loadings() - Bounded participant loadings with credible intervals
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compute_flags() - Flag probabilities with an explicit unclassified state
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compute_zscores() - Statement scores with credible intervals
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compute_factor_array() - Quota-respecting factor arrays
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compute_qdc() - Distinguishing and consensus verdicts
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factor_characteristics() - Factor characteristics
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crib_sheet() - Extreme-placement probabilities per statement and factor
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claims() - Selected claims at a common false-discovery level
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check_fit() - Posterior-predictive checks of the fitted model
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check_persons() - The person check against mixed-replication bands
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fit_ladder() - Fit the model over a ladder of K
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select_k() - Choose K by the two-signal rule
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loo_ladder() - PSIS-LOO across the ladder, as directional corroboration
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loglik_person() - Person-level partition log-likelihoods
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rotate_factors() - Rotate every aligned draw toward a target
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flip_factor() - Flip the pole of one factor
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rename_factors() - Rename the factors
Plots
Base-graphics views of the fit; ggplot2::autoplot() serves the flagship four (loadings, flags, contrasts, array).
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plot_loading_posterior()plot(<bayesqm_fit>) - Bounded loadings with credible intervals
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plot_sorts() - Preview every participant's sort
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plot_zscores() - Statement scores across factors, whole panel
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plot_statement()plot_zscore_posterior() - One statement, in depth
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plot_membership()plot_flags() - Flag probabilities with the unclassified state
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plot_factor_array() - The factor array on its grid
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plot_dist_cons()plot_contrasts() - Statement contrasts between two factors
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plot_choice_k() - The two-signal choice-of-K display
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plot_person_check() - The person check against the mixed bands
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plot_tucker()plot_convergence() - Convergence and alignment view
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plot_ppc() - Posterior-predictive check display
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bayesqm_colors()bayesqm_set_colors() - Get or set the bayesqm colour scheme
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save_bayesqm_plot() - Save a bayesqm plot to file
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caption_bayesqm() - Caption text for figures from a fit
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coef(<bayesqm_fit>) - Posterior-mean bounded loadings
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fitted(<bayesqm_fit>) - Posterior-mean reconstruction on the utility scale
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sigma(<bayesqm_fit>) - Posterior-mean loading scales
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posterior_interval() - Posterior interval generic
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posterior_interval(<bayesqm_fit>) - Credible intervals for bayesqm_fit parameters
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prior_summary() - Prior summary generic
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prior_summary(<bayesqm_fit>) - Prior summary for a bayesqm_fit
Data: import and construction
Readers for CSV/Excel/PQMethod/Ken-Q/KADE/HTMLQ, the qsort_data object, and the shipped example panel.
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read_qsort()read_qsort_csv()read_qsort_excel()read_pqmethod()read_kenq()read_kenq_excel()read_kade_zip()read_easyhtml_firebase()read_statements() - Read Q-sort data from file
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import.pqmethod()import.htmlq()import.kenq()import.easyhtmlq() - qmethod-style import aliases
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qsort_data()validate_qsort()check_distribution()infer_distribution()parse_distribution() - Construct a validated qsort_data object
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print(<qsort_data>)summary(<qsort_data>)as.matrix(<qsort_data>) - Print, summary, and matrix conversion for qsort_data
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obesity_sorts - Childhood obesity Q sorts
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grizzly_sorts - Grizzly bear reintroduction Q sorts
Demonstration and synthetic panels
A fast demonstration fit, synthetic panels with known truth, and recovery measures for method checks.
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demo_fit() - A small demonstration fit
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generate_data()generate_loadings()generate_noise()discretize_to_grid()get_distribution() - Simulate Q-sort data
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assess_recovery()assess_classification() - Simulation-study assessment helpers
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tucker_congruence()procrustes_rotation() - Tucker's congruence and orthogonal Procrustes rotation
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run_bayes()plot_hyper()select_k_peak()select_k_sivula()compute_dominant_prob()compute_dominant_sign()compute_threshold_prob()classify_membership()compute_divergence()critical_delta()suggest_delta()compute_posterior_scalars()demo_run()plot_elpd()make_elpd_diff()make_ppc_ridge()make_dominant_panel() - Defunct 0.1.0 functions