This repository contains data and code supporting the following paper:
Hu, X., Zheng, J., Su, N., Fan, T., Yang, C., Yin, Y., Fleming, S. M., & Luo, L. (in prep). A Bayesian inference model for metamemory.
Script and data files are included in the repository to enable replication of data simulation and analyses.
PLEASE NOTE: BIM uses the Particle Swarm optimization algorithm to estimate free parameters, which requires MATLAB version R2014b or later.
The folder BIM contains the core functions of BIM, which can be fitted to data from recall or recognition tasks with continuous or discrete confidence ratings.
- Run fit_bim.m for data from recall tasks with continuous confidence ratings (on a 0-100 continuous scale).
- Run fit_bim_bins.m for data from recall tasks with discrete confidence ratings (on a scale with no less than 3 points).
- Run fit_bim_recog.m for data from recognition tasks with continuous confidence ratings (on a 0-100 continuous scale).
- Run fit_bim_bins_recog.m for data from recognition tasks with discrete confidence ratings (on a scale with no less than 3 points).
The folder simulation contains the scripts for the data simulation and analyses described in the section "Data Simulation and Parameter Recovery" of our paper.
The folder studies contains the raw data and scripts for data analyses in Studies 1-4.
The folder extended contains the scripts for simulating data from the extended BIM.