| hsdt | Fit a hierarchical signal detection theory model |
| latent_cor | Test the three core hypotheses of a hierarchical SDT model |
| latent_regression | Test the three core hypotheses of a hierarchical SDT model |
| meyen_split | Dichotomize response times into binary choices |
| plot.hsdt | Diagnostic and analytical plots for hierarchical SDT models |
| plot.usdt_bf | Plot the prior and posterior of tested quantities |
| plot.usdt_mdes | Plot a population, its power, its smallest effects or a plan |
| plot.usdt_plan | Plot a population, its power, its smallest effects or a plan |
| plot.usdt_population | Plot a population, its power, its smallest effects or a plan |
| plot.usdt_power | Plot a population, its power, its smallest effects or a plan |
| plot.usdt_priors | Prior predictive check for the Bayesian hierarchical SDT model |
| plot_power | Plot a population, its power, its smallest effects or a plan |
| print.hsdt | Fit a hierarchical signal detection theory model |
| print.summary.usdt_power | Power of a planned uSDT study |
| print.usdt_bf | Bayes factors for the hypotheses of a Bayesian hierarchical SDT model |
| print.usdt_data | Prepare data for hierarchical SDT models |
| print.usdt_equivalence | Equivalence, non-inferiority and minimal-effect tests |
| print.usdt_mdes | Smallest effect a uSDT study detects |
| print.usdt_plan | Plan the subjects and trials of a uSDT study |
| print.usdt_population | Population values for planning a uSDT study |
| print.usdt_power | Power of a planned uSDT study |
| print.usdt_priors | Priors for the Bayesian hierarchical SDT model |
| print.usdt_reliability | Reliability of awareness and influence task measures |
| sdt_moments | Signal detection measures for each subject |
| sensitivity_diff | Test the three core hypotheses of a hierarchical SDT model |
| summary.hsdt | Fit a hierarchical signal detection theory model |
| summary.usdt_power | Power of a planned uSDT study |
| summary.usdt_reliability | Reliability of awareness and influence task measures |
| update.usdt_population | Population values for planning a uSDT study |
| usdt_aggregate | Count binary responses by group |
| usdt_bf | Bayes factors for the hypotheses of a Bayesian hierarchical SDT model |
| usdt_boot | Parametric bootstrap intervals for hierarchical SDT models |
| usdt_data | Prepare data for hierarchical SDT models |
| usdt_data_long | Prepare data for hierarchical SDT models |
| usdt_data_tasks | Prepare data for hierarchical SDT models |
| usdt_equivalence | Equivalence, non-inferiority and minimal-effect tests |
| usdt_hypotheses | Test the three core hypotheses of a hierarchical SDT model |
| usdt_mdes | Smallest effect a uSDT study detects |
| usdt_plan | Plan the subjects and trials of a uSDT study |
| usdt_population | Population values for planning a uSDT study |
| usdt_power | Power of a planned uSDT study |
| usdt_priors | Priors for the Bayesian hierarchical SDT model |
| usdt_reliability | Reliability of awareness and influence task measures |
| usdt_tests | Test the three core hypotheses of a hierarchical SDT model |
| vadillo_awareness | Awareness data from a probabilistic cuing experiment |
| vadillo_cuing | Cuing data from a probabilistic cuing experiment |