Human and AI classifications of images (ImageNet16H). This OSF repository contains the data from Steyvers et al. (2022). Bayesian Modeling of Human-AI Complementarity, Proceedings of the National Academy of Sciences. The data consists of 28,997 human classifications of images from a total of 145 participants. In addition, the data set includes classifications from a number of convolutional neural networks for the same set of images.
Lumosity cognitive training data. This OSF repository contains the data from: Steyvers, M, and Schafer, B. (2021). Inferring Latent Learning Factors in Large-Scale Cognitive Training Data, Nature Human Behaviour. The data set includes the gameplay data for over 36K users across 50+ cognitive tasks. The raw data contains performance scores at the gameplay level and do not include the individual decisions made within a particular gameplay.
Lumosity Task Switching Data and Modeling Code. This OSF repository contains the data and code from: Steyvers, M, Hawkins, G., Karayanidis, F. and Brown, S. (2019). The Dynamics of Task Switching: Modeling Practice and Age Effects in Large-Scale Data. Proceedings of the National Academy of Sciences. The data set that we are working with includes the gameplay data for a sample of users who play Ebb and Flow, a task switching game on Lumosity. This is a game designed to test the ability to switch between different tasks. The raw data is described at the individual trial level (i.e., individual decisions within a particular gameplay event) and include response time, accuracy, as well as identifiers that describe the particular stimulus display and type of condition associated with the trial.
General Knowledge Questionnaire Data. This OSF repository contains data from Bennett, Benjamin, Mistry, P.K., and Steyvers (2018) where individuals answer general knowledge questions that are either chosen by the individuals (from a larger pool) or are randomly selected for the individuals.
Matjags. This interface allows JAGS (“Just Another Gibbs Sampler”) to be used in combination with Matlab. [github]. Note: I no longer actively maintain this software.
Matlab Topic Modeling Toolbox. Somewhat outdated Matlab code that runs a number of topic models. [zip file]. Note: I no longer actively maintain this software.
JAGS code for Bayesian Signal Detection Model to Evaluate Probabilistic Forecasts. JAGS code for model in section 3.1 of Steyvers et al. (2014) paper “Evaluating Probabilistic Forecasts with Bayesian Signal
Detection Models“.
Programming online experiments that run locally in Amazon Mechanical Turk. Tutorial