Man pages for qdercon/pstpipeline
Probabilistic Selection Task (PST) pipeline: parsing, analysis, simulation, and plotting
| check_learning_models | Diagnostic plots and fit metrics for training and test data... |
| cmdstan_glm | Bayesian generalized linear models via CmdStan |
| compare_block_diffs | Compare learning parameters between groups over different... |
| example_data | Example probabilistic selection task data |
| fit_learning_model | General function to run Bayesian models using cmdstanr |
| generate_posterior_quantities | Generate posterior quantities following MCMC |
| get_affect_ppc | Extract posterior predictions from affect data models and... |
| get_preds_by_chain | Get and store posterior predictions for training data |
| import_multiple | JATOS text file parsing function (multiple results) |
| import_single | JATOS text file parsing function (single result) |
| make_par_df | Construct a tibble containing individual-level parameter... |
| parameter_glm | Quantify and plot associations between learning parameters... |
| plot_affect | Plot an individual's mean posterior predictions compared to... |
| plot_factors | Various plots for factor prediction and derivation |
| plot_glm | Plot associations between Q-learning model parameters and... |
| plot_import | Plot raw experiment data |
| plot_ppc | Plot posterior predictions against observed data |
| plot_raincloud | Raincloud plots |
| plot_recovery | Plots to check parameter recovery |
| quantile_hdi | Compute quantiles of a probability distrbution based on... |
| simulate_QL | Simulate data from single and dual learning rate Q-learning... |
| take_subsample | Helper function to take a subsample of our parsed list (for... |
