| 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 |
| print.hsdt | Fit a hierarchical signal detection theory model |
| print.usdt_data | Prepare data for hierarchical SDT models |
| print.usdt_reliability | Reliability of direct and indirect 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_reliability | Reliability of direct and indirect task measures |
| 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_hypotheses | Test the three core hypotheses of a hierarchical SDT model |
| usdt_reliability | Reliability of direct and indirect 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 |