Bayesian estimation of multinomial processing tree models with heterogeneity in participants and items.

@article{Matzke2015BayesianEO,
  title={Bayesian estimation of multinomial processing tree models with heterogeneity in participants and items.},
  author={Dora Matzke and Conor V. Dolan and William H. Batchelder and Eric-Jan Wagenmakers},
  journal={Psychometrika},
  year={2015},
  volume={80 1},
  pages={205-35}
}
Multinomial processing tree (MPT) models are theoretically motivated stochastic models for the analysis of categorical data. Here we focus on a crossed-random effects extension of the Bayesian latent-trait pair-clustering MPT model. Our approach assumes that participant and item effects combine additively on the probit scale and postulates (multivariate) normal distributions for the random effects. We provide a WinBUGS implementation of the crossed-random effects pair-clustering model and an… CONTINUE READING