The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Bayesian alternatives for common null-hypothesis significance tests in psychiatry: a non-technical guide using JASP
Open accessAbstract
BACKGROUND: Despite its popularity as an inferential framework, classical null hypothesis significance testing (NHST) has several restrictions. Bayesian analysis can be used to complement NHST, however, this approach has been underutilized largely due to a dearth of accessible software options. JASP is a recently developed open-source statistical package that facilitates both Bayesian and NHST analysis using a graphical interface. This article provides an applied introduction to Bayesian inference with Bayes factors using JASP. METHODS: We use JASP to compare and contrast Bayesian alternatives for several common classical null hypothesis significance tests: correlations, frequency distributions, t-tests, ANCOVAs, and ANOVAs. These examples are also used to illustrate the strengths and limitations of both NHST and Bayesian hypothesis testing. RESULTS: A comparison of NHST and Bayesian inferential frameworks demonstrates that Bayes factors can complement p-values by providing additional information for hypothesis testing. Namely, Bayes factors can quantify relative evidence for both alternative and null hypotheses. Moreover, the magnitude of this evidence can be presented as an easy-to-interpret odds ratio. CONCLUSIONS: While Bayesian analysis is by no means a new method, this type of statistical inference has been largely inaccessible for most psychiatry researchers. JASP provides a straightforward means of performing reproducible Bayesian hypothesis tests using a graphical "point and click" environment that will be familiar to researchers conversant with other graphical statistical packages, such as SPSS.
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Cites
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Bayesian t tests for accepting and rejecting the null hypothesis
Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009) · Psychonomic Bulletin & Review · doi:10.3758/pbr.16.2.225 · Cited by 3,688
A manifesto for reproducible science
Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie du Sert, N., Simonsohn, U., Wagenmakers, E.-J., Ware, J. J., & Ioannidis, J. P. A. (2017) · Nature Human Behaviour · doi:10.1038/s41562-016-0021 · Cited by 3,397
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016) · European Journal of Epidemiology · doi:10.1007/s10654-016-0149-3 · Cited by 3,200
Schuirmann, D. J. (1987) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1007/bf01068419 · Cited by 2,696
A practical solution to the pervasive problems ofp values
Wagenmakers, E.-J. (2007) · Psychonomic Bulletin & Review · doi:10.3758/bf03194105 · Cited by 2,490
Lakens, D. (2017) · Social Psychological and Personality Science · doi:10.1177/1948550617697177 · Cited by 2,161
The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis
Hoenig, J. M., & Heisey, D. M. (2001) · The American Statistician · doi:10.1198/000313001300339897 · Cited by 2,046 · cited 1×
“set is sensitive enough to detect a true effect when using p-values [8].”
BackgroundUsing Bayes to get the most out of non-significant results
Dienes, Z. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00781 · Cited by 1,998
Bayesian Cognitive Modeling: A Practical Course
Lee, M. D., & Wagenmakers, E.-J. (2014) · doi:10.1017/cbo9781139087759 · Cited by 1,795
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Le Mau, T., Hoemann, K., Lyons, S. H., Fugate, J. M. B., Brown, E. N., Gendron, M., & Barrett, L. F. (2021) · Nature Communications · doi:10.1038/s41467-021-25352-6 · Cited by 74
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Metadata
- Authors
- Quintana, D. S., & Williams, D. R.
- Venue
- BMC Psychiatry
- Published
- 2018-06-07
- Volume
- 18
- Issue
- 1
- Pages
- 178-178
- ISSN
- 1471-244X (ISSN-L)
- OpenAlex
- W2780349532
- Cited by
- 408
- References
- 15
- FWCI
- 36.48
- Type
- journal article
- Language
- en
- Open access
- gold
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