Evidence map›Paper›PMID 28779455›Full record

ArticlePsychonomic bulletin & review2018

Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications.

Eric-Jan Wagenmakers, Maarten Marsman, Tahira Jamil, Alexander Ly, Josine Verhagen, Jonathon Love, Ravi Selker, Quentin F Gronau, Martin Šmíra, Sacha Epskamp and 3 more

Abstract read
In one paragraph

Article in Psychonomic bulletin & review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 570 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
570citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

570 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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510 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Eric-Jan WagenmakersDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands. EJ.Wagenmakers@gmail.com.
Maarten MarsmanDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Tahira JamilDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Alexander LyDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Josine VerhagenDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Jonathon LoveDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Ravi SelkerDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Quentin F GronauDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Martin ŠmíraMasaryk University, Brno, Czech Republic.
Sacha EpskampDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Dora MatzkeDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.
Jeffrey N RouderUniversity of Missouri, Columbia, MO, USA.
Richard D MoreyCardiff University, Cardiff, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers. For instance, Bayesian hypothesis testing allows researchers to quantify evidence and monitor its progression as data come in, without needing to know the intention with which the data were collected. We end by countering several objections to Bayesian hypothesis testing. Part II of this series discusses JASP, a free and open source software program that makes it easy to conduct Bayesian estimation and testing for a range of popular statistical scenarios (Wagenmakers et al. this issue).

Indexed as

Bayes TheoremPsychologyHumansResearch DesignBayes factorHypothesis testPosterior distributionStatistical evidence

Identifiers

PMID28779455
PMCPMC5862936

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.