Preprint

The bhsdtr package: a general-purpose method of Bayesian inference for Signal Detection Theory models

This article is a preprint and has not been certified by peer review [What does this mean?].

Author(s) / Creator(s)

Paulewicz, Borysław
Blaut, Agata

Other kind(s) of contributor

SWPS University, Faculty in Katowice
Jagiellonian University

Abstract / Description

We describe a novel method of Bayesian inference for hierarchical or non-hierarchical equal variance normal Signal Detection Theory models with one or more criteria. The method is implemented as an open-source R package that uses the state-of-the-art Stan platform for sampling from posterior distributions. Our method can accommodate binary responses as well as additional ratings and an arbitrary number of nested or crossed random grouping factors. The SDT parameters can be regressed on additional predictors within the same model via intermediate unconstrained parameters, and the model can be extended by using automatically generated human-readable Stan code as a template. In the paper we explain how our method improves on other similar available methods, we give an overview of the package, demonstrate its use by providing a real-study data analysis walk-through, and show that the model successfully recovers known parameter values when fitted to simulated data. We also demonstrate that ignoring a hierarchical data structure may lead to severely biased estimates when fitting Signal Detection Theory models.
Preprint for: Paulewicz, B., Blaut, A. The bhsdtr package: a general-purpose method of Bayesian inference for signal detection theory models. Behav Res 52, 2122–2141 (2020). https://doi.org/10.3758/s13428-020-01370-y

Keyword(s)

Signal Detection Theory Bayesian Inference Hierarchical Models

Persistent Identifier

Date of first publication

2020

Publisher

PsychArchives

Is version of

Citation

Paulewicz, B., & Blaut, A. (2020). The bhsdtr package: a general-purpose method of Bayesian inference for Signal Detection Theory models. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.2725
  • Author(s) / Creator(s)
    Paulewicz, Borysław
  • Author(s) / Creator(s)
    Blaut, Agata
  • Other kind(s) of contributor
    SWPS University, Faculty in Katowice
    en
  • Other kind(s) of contributor
    Jagiellonian University
    en
  • PsychArchives acquisition timestamp
    2020-01-21T13:12:23Z
  • Made available on
    2020-01-21T13:12:23Z
  • Date of first publication
    2020
  • Abstract / Description
    We describe a novel method of Bayesian inference for hierarchical or non-hierarchical equal variance normal Signal Detection Theory models with one or more criteria. The method is implemented as an open-source R package that uses the state-of-the-art Stan platform for sampling from posterior distributions. Our method can accommodate binary responses as well as additional ratings and an arbitrary number of nested or crossed random grouping factors. The SDT parameters can be regressed on additional predictors within the same model via intermediate unconstrained parameters, and the model can be extended by using automatically generated human-readable Stan code as a template. In the paper we explain how our method improves on other similar available methods, we give an overview of the package, demonstrate its use by providing a real-study data analysis walk-through, and show that the model successfully recovers known parameter values when fitted to simulated data. We also demonstrate that ignoring a hierarchical data structure may lead to severely biased estimates when fitting Signal Detection Theory models.
    en
  • Abstract / Description
    Preprint for: Paulewicz, B., Blaut, A. The bhsdtr package: a general-purpose method of Bayesian inference for signal detection theory models. Behav Res 52, 2122–2141 (2020). https://doi.org/10.3758/s13428-020-01370-y
    en
  • Publication status
    other
    en
  • Review status
    notReviewed
    en
  • Sponsorship
    This work was supported by the National Science Centre, Poland SONATA grant given to BP (2013/09/D/HS6/02792).
    en
  • Citation
    Paulewicz, B., & Blaut, A. (2020). The bhsdtr package: a general-purpose method of Bayesian inference for Signal Detection Theory models. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.2725
    en
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/2339
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.2725
  • Language of content
    eng
  • Publisher
    PsychArchives
    en
  • Is version of
    https://doi.org/10.3758/s13428-020-01370-y
  • Requires
    https://github.com/boryspaulewicz/bhsdtr
  • Is related to
    https://doi.org/10.3758/s13428-020-01370-y
  • Keyword(s)
    Signal Detection Theory
    en
  • Keyword(s)
    Bayesian Inference
    en
  • Keyword(s)
    Hierarchical Models
    en
  • Dewey Decimal Classification number(s)
    150
  • Title
    The bhsdtr package: a general-purpose method of Bayesian inference for Signal Detection Theory models
    en
  • DRO type
    preprint
    en