Editors’ introduction to the special issue “Bayes factors for testing hypotheses in psychological research: Practical relevance and new developments”

J. Mulder, Eric-Jan Wagenmakers

Research output: Contribution to journalEditorialScientificpeer-review

Abstract

In order to test their hypotheses, psychologists increasingly favor the Bayes factor , the standard Bayesian measure of relative evidence between two competing statistical models. The Bayes factor has an intuitive interpretation and allows a comparison between any two models, even models that are complex and nonnested. In this introduction to the special issue “Bayes factors for Testing Hypotheses in Psychological Research: Practical Relevance and New Developments”, we first highlight the basic properties of the Bayes factor, stressing its advantages over classical significance testing. Next, we briefly discuss statistical software packages that are useful for researchers who wish to make the transition from p values to Bayes factors. We end by providing an overview of the contributions to this special issue. The contributions fall in three partly overlapping categories: those that present new philosophical insights, those that provide methodological innovations, and those that demonstrate practical applications.
Original languageEnglish
Pages (from-to)1-5
JournalJournal of Mathematical Psychology
Volume72
DOIs
Publication statusPublished - 2016

Fingerprint

Testing Hypotheses
Bayes Factor
Testing
Statistical Models
Software packages
Innovation
Statistical Software
Hypothesis Test
p-Value
Software Package
Statistical Model
Overlapping
Intuitive
Relevance
Model
Demonstrate

Keywords

  • Bayes factors; p values; Psychology

Cite this

@article{d00c034c6c734fce87843d7e33379309,
title = "Editors’ introduction to the special issue “Bayes factors for testing hypotheses in psychological research: Practical relevance and new developments”",
abstract = "In order to test their hypotheses, psychologists increasingly favor the Bayes factor , the standard Bayesian measure of relative evidence between two competing statistical models. The Bayes factor has an intuitive interpretation and allows a comparison between any two models, even models that are complex and nonnested. In this introduction to the special issue “Bayes factors for Testing Hypotheses in Psychological Research: Practical Relevance and New Developments”, we first highlight the basic properties of the Bayes factor, stressing its advantages over classical significance testing. Next, we briefly discuss statistical software packages that are useful for researchers who wish to make the transition from p values to Bayes factors. We end by providing an overview of the contributions to this special issue. The contributions fall in three partly overlapping categories: those that present new philosophical insights, those that provide methodological innovations, and those that demonstrate practical applications.",
keywords = "Bayes factors; p values; Psychology",
author = "J. Mulder and Eric-Jan Wagenmakers",
year = "2016",
doi = "10.1016/j.jmp.2016.01.002",
language = "English",
volume = "72",
pages = "1--5",
journal = "Journal of Mathematical Psychology",
issn = "0022-2496",
publisher = "ACADEMIC PRESS INC ELSEVIER SCIENCE",

}

Editors’ introduction to the special issue “Bayes factors for testing hypotheses in psychological research: Practical relevance and new developments”. / Mulder, J.; Wagenmakers, Eric-Jan.

In: Journal of Mathematical Psychology, Vol. 72, 2016, p. 1-5.

Research output: Contribution to journalEditorialScientificpeer-review

TY - JOUR

T1 - Editors’ introduction to the special issue “Bayes factors for testing hypotheses in psychological research: Practical relevance and new developments”

AU - Mulder, J.

AU - Wagenmakers, Eric-Jan

PY - 2016

Y1 - 2016

N2 - In order to test their hypotheses, psychologists increasingly favor the Bayes factor , the standard Bayesian measure of relative evidence between two competing statistical models. The Bayes factor has an intuitive interpretation and allows a comparison between any two models, even models that are complex and nonnested. In this introduction to the special issue “Bayes factors for Testing Hypotheses in Psychological Research: Practical Relevance and New Developments”, we first highlight the basic properties of the Bayes factor, stressing its advantages over classical significance testing. Next, we briefly discuss statistical software packages that are useful for researchers who wish to make the transition from p values to Bayes factors. We end by providing an overview of the contributions to this special issue. The contributions fall in three partly overlapping categories: those that present new philosophical insights, those that provide methodological innovations, and those that demonstrate practical applications.

AB - In order to test their hypotheses, psychologists increasingly favor the Bayes factor , the standard Bayesian measure of relative evidence between two competing statistical models. The Bayes factor has an intuitive interpretation and allows a comparison between any two models, even models that are complex and nonnested. In this introduction to the special issue “Bayes factors for Testing Hypotheses in Psychological Research: Practical Relevance and New Developments”, we first highlight the basic properties of the Bayes factor, stressing its advantages over classical significance testing. Next, we briefly discuss statistical software packages that are useful for researchers who wish to make the transition from p values to Bayes factors. We end by providing an overview of the contributions to this special issue. The contributions fall in three partly overlapping categories: those that present new philosophical insights, those that provide methodological innovations, and those that demonstrate practical applications.

KW - Bayes factors; p values; Psychology

U2 - 10.1016/j.jmp.2016.01.002

DO - 10.1016/j.jmp.2016.01.002

M3 - Editorial

VL - 72

SP - 1

EP - 5

JO - Journal of Mathematical Psychology

JF - Journal of Mathematical Psychology

SN - 0022-2496

ER -