Psychonomic Bulletin & Review

, Volume 25, Issue 1, pp 77–101 | Cite as

Bayesian inference for psychology, part III: Parameter estimation in nonstandard models

Article

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/.

Keywords

WinBUGS JAGS Stan Bayesian estimation Bayesian inference 

Notes

Acknowledgements

The authors thank Eric-Jan Wagenmakers for helpful comments during the writing of this article. DM was supported by a Veni grant #451-15-010 from the Netherlands Organization of Scientific Research (NWO). UB was supported by an NWO Research Talent grant #406-12-125. JV was supported by NSF grants #1230118 and #1534472 from the Methods, Measurements, and Statistics panel and John Templeton Foundation grant #48192.

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Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  • Dora Matzke
    • 1
  • Udo Boehm
    • 2
  • Joachim Vandekerckhove
    • 3
  1. 1.University of AmsterdamAmsterdamNetherlands
  2. 2.University of GroningenGroningenNetherlands
  3. 3.University of CaliforniaIrvineUSA

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