Psychonomic Bulletin & Review· 2017Q1
Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications
- 1,722citations
- Q1SCImago
- 2017year
Short summary
Bayesian inference offers a superior alternative to classical p-value and confidence interval methods for psychological research, enabling quantification of evidence and continuous monitoring as data accrues.
AI-generated from the title and abstract; the full text is not read.
Key points
- Bayesian inference provides alternatives to classical confidence intervals and p-values.
- Ten prominent advantages of the Bayesian approach are outlined.
- Bayesian hypothesis testing allows for quantifying evidence and monitoring its progression as data arrives.
- The paper counters several objections to Bayesian hypothesis testing.
AI-generated from the title and abstract; the full text is not read.
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).
The authors' abstract, as published at the source. Psychonomic Bulletin & Review, 2017 · DOI ↗
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Field: Experimental and Cognitive Psychology
Experimental and Cognitive PsychologyPsychology