R: Bayesian Q Methodology: Probabilistic Factor Analysis

# Bayesian Q Methodology: Probabilistic Factor Analysis

## Documentation for package ‘bayesqm’ version 0.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

as.array.bayesqm_fit | Standard R accessors for bayesqm_fit
as.data.frame.bayesqm_fit | Standard R accessors for bayesqm_fit
as.matrix.bayesqm_fit | Standard R accessors for bayesqm_fit
as.matrix.qsort_data | Print, summary, and matrix conversion for qsort_data
assess_classification | Simulation-study assessment helpers
assess_recovery | Simulation-study assessment helpers
bayesqm-colors | Get or set the bayesqm colour scheme
bayesqm-fit-accessors | Standard R accessors for bayesqm_fit
bayesqm-fit-methods | Print and summary methods for bayesqm_fit and bayesqm_run
bayesqm-membership | Probabilistic factor-membership and divergence summaries
bayesqm_colors | Get or set the bayesqm colour scheme
bayesqm_set_colors | Get or set the bayesqm colour scheme
caption_bayesqm | Dynamic figure caption for a bayesqm_fit
check_distribution | Construct a validated qsort_data object
classify_membership | Probabilistic factor-membership and divergence summaries
coef.bayesqm_fit | Standard R accessors for bayesqm_fit
compute_divergence | Probabilistic factor-membership and divergence summaries
compute_dominant_prob | Probabilistic factor-membership and divergence summaries
compute_dominant_sign | Probabilistic factor-membership and divergence summaries
compute_factor_array | Factor arrays on the forced Q-sort distribution
compute_loadings | Posterior summary of participant factor loadings
compute_posterior_scalars | Posterior summary of scalar hyperparameters
compute_threshold_prob | Probabilistic factor-membership and divergence summaries
compute_zscores | Posterior summary of statement factor z-scores
critical_delta | Reliability-adjusted critical difference (default 'delta')
demo_fit | A synthetic bayesqm_fit for examples and tutorials
demo_run | A synthetic bayesqm_run for examples and tutorials
discretize_to_grid | Simulate Q-sort data
family.bayesqm_fit | Standard R accessors for bayesqm_fit
fitted.bayesqm_fit | Standard R accessors for bayesqm_fit
fit_bayesian | Fit a Bayesian Q-methodology factor model
generate_data | Simulate Q-sort data
generate_loadings | Simulate Q-sort data
generate_noise | Simulate Q-sort data
get_distribution | Simulate Q-sort data
import-aliases | qmethod-style import aliases
import.easyhtmlq | qmethod-style import aliases
import.htmlq | qmethod-style import aliases
import.kenq | qmethod-style import aliases
import.pqmethod | qmethod-style import aliases
infer_distribution | Construct a validated qsort_data object
make_dominant_panel | Probabilistic dominant-factor panel
make_elpd_diff | Delta-ELPD plot with Sivula band, peak, and adopted-K annotations
make_ppc_ridge | Posterior predictive RMSE ridgeline across K
matchalign | MatchAlign post-processing for Bayesian factor draws
nobs.bayesqm_fit | Standard R accessors for bayesqm_fit
parse_distribution | Construct a validated qsort_data object
plot.bayesqm_fit | Factor-score dotchart for a bayesqm_fit
plot_dist_cons | Distinguishing/consensus divergence forest
plot_elpd | ELPD across K with peak and Sivula annotations
plot_hyper | Hyperparameter posterior densities
plot_loading_posterior | Loading forest with 50 and 95 percent credible intervals
plot_membership | Dominant-factor posterior-probability heatmap
plot_ppc | Posterior predictive check on the correlation-matrix RMSE
plot_tucker | MatchAlign Tucker's phi distribution by factor
plot_zscore_posterior | Per-statement factor-score posterior across factors
posterior_interval.bayesqm_fit | Credible intervals for bayesqm_fit parameters
print.bayesqm_family | Standard R accessors for bayesqm_fit
print.bayesqm_fit | Print and summary methods for bayesqm_fit and bayesqm_run
print.bayesqm_prior | Prior summary for a bayesqm_fit
print.bayesqm_run | Print and summary methods for bayesqm_fit and bayesqm_run
print.qsort_data | Print, summary, and matrix conversion for qsort_data
prior_summary.bayesqm_fit | Prior summary for a bayesqm_fit
procrustes_rotation | Tucker's congruence and orthogonal Procrustes rotation
qsort_data | Construct a validated qsort_data object
qsort_data-methods | Print, summary, and matrix conversion for qsort_data
read_easyhtml_firebase | Read Q-sort data from file
read_kade_zip | Read Q-sort data from file
read_kenq | Read Q-sort data from file
read_kenq_excel | Read Q-sort data from file
read_pqmethod | Read Q-sort data from file
read_qsort | Read Q-sort data from file
read_qsort_csv | Read Q-sort data from file
read_qsort_excel | Read Q-sort data from file
read_statements | Read Q-sort data from file
rename_factors | Rename factors consistently across a bayesqm_fit
residuals.bayesqm_fit | Standard R accessors for bayesqm_fit
run_bayes | Fit the model across a range of K
save_bayesqm_plot | Save a bayesqm plot to file
select_k_peak | Fit the model across a range of K
select_k_sivula | Fit the model across a range of K
sigma.bayesqm_fit | Standard R accessors for bayesqm_fit
suggest_delta | Suggested separation 'delta' from the forced distribution
summary.bayesqm_fit | Print and summary methods for bayesqm_fit and bayesqm_run
summary.bayesqm_run | Print and summary methods for bayesqm_fit and bayesqm_run
summary.qsort_data | Print, summary, and matrix conversion for qsort_data
tucker_congruence | Tucker's congruence and orthogonal Procrustes rotation
update.bayesqm_fit | Standard R accessors for bayesqm_fit
validate_qsort | Construct a validated qsort_data object