Tutorials¶
- Lesson 1: An Introduction to Psychophysical Modelling
- Lesson 2: Risky Choice — Psychometric Functions and the Noise–Risk Link
- Lesson 3: Stake effects and presentation order — de Hollander et al. (2024, bioRxiv)
- Lesson 4: Flexible Noise Curves —
FlexibleNoiseComparisonModelandFlexibleNoiseRiskModel - Lesson 5: Why Hierarchical Modelling Beats Maximum Likelihood
- Lesson 8: DDM vs probit on the Garcia magnitude task
- Lesson 9: Choice + Reaction Time Models — DDM and Race-Diffusion
- Lesson 10: Fixed vs random effects (
fixed_regressors/random_regressors)