Bayesian Inference in Psychology, Part III: Bayesian parameter estimation in nonstandard models

Abstract

We demonstrate the use of three popular Bayesian software packages that enable researchers to estimate parameters in a broad class of models that are commonly used in psychological research. We focus on WinBUGS, JAGS, and Stan, and show how they can be interfaced from R and MATLAB. We illustrate the use of the packages through two fully worked examples; the examples involve a simple univariate linear regression and fitting a multinomial processing tree model to data from a classic false-memory experiment. We conclude with a comparison of the strengths and weaknesses of the packages. Our example code, data, and this text are available via https://osf.io/ucmaz/.

Citation

Matzke, D., Boehm, U., & Vandekerckhove, J. (2018). Bayesian Inference in Psychology, Part III: Bayesian parameter estimation in nonstandard models. Psychonomic Bulletin & Review, 25, 77–101.

Bibtex

@article{matzke_etal:2018:nonstandard,
    title   = {{B}ayesian {I}nference in {P}sychology, {P}art {I}{I}{I}: {B}ayesian parameter estimation in nonstandard models},
    author  = {Matzke, Dora and Boehm, Udo and Vandekerckhove, Joachim},
    year    = {2018},
    journal = {Psychonomic Bulletin \& Review},
    volume  = {25},
    pages   = {77--101}
}