The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index.
An Introduction to Bayesian Hypothesis Testing for Management Research
Open accessAbstract
In management research, empirical data are often analyzed using p-value null hypothesis significance testing (pNHST). Here we outline the conceptual and practical advantages of an alternative analysis method: Bayesian hypothesis testing and model selection using the Bayes factor. In contrast to pNHST, Bayes factors allow researchers to quantify evidence in favor of the null hypothesis. Also, Bayes factors do not require adjustment for the intention with which the data were collected. The use of Bayes factors is demonstrated through an extended example for hierarchical regression based on the design of an experiment recently published in the Journal of Management. This example also highlights the fact that p values overestimate the evidence against the null hypothesis, misleading researchers into believing that their findings are more reliable than is warranted by the data.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
Testing Structural Equation Models.
Mueller, C. W., Bollen, K. A., & Long, J. S. (1994) · Contemporary Sociology · doi:10.2307/2074955 · Cited by 14,120
Data Analysis Using Regression and Multilevel/Hierarchical Models
Gelman, A., & Hill, J. (2006) · doi:10.1017/cbo9780511790942 · Cited by 13,597
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences.
Henry, N. W., Cohen, J., & Cohen, P. (1977) · Contemporary Sociology · doi:10.2307/2064799 · Cited by 7,089
Bayesian model selection in social research
Raftery, A. E. (1995) · Sociological Methodology · doi:10.2307/271063 · Cited by 6,823
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011) · Psychological Science · doi:10.1177/0956797611417632 · Cited by 6,567
Journal of The American Statistical Association
Fienberg, S. E. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1317 · Cited by 6,125
Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999) · Statistical Science · doi:10.1214/ss/1009212519 · Cited by 4,118
Cohen, J. (1994) · American Psychologist · doi:10.1037/0003-066x.49.12.997 · Cited by 4,003
Cited by
Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications
Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., et al. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1343-3 · Cited by 1,627
Self-citationArtificial intelligence and the changing sources of competitive advantage
Krakowski, S., Luger, J., & Raisch, S. (2023) · Strategic Management Journal · doi:10.1002/smj.3387 · Cited by 594
Ly, A., Verhagen, J., & Wagenmakers, E.-J. (2016) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2015.06.004 · Cited by 384
Self-citationTossell, C. C., Tenhundfeld, N. L., Momen, A., Cooley, K., & de Visser, E. J. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3355015 · Cited by 218
Questions About Questionable Research Practices in the Field of Management: A Guest Commentary
Banks, G. C., O’Boyle, E. H., Pollack, J. M., White, C. D., Batchelor, J. H., Whelpley, C. E., Abston, K. A., Bennett, A. A., & Adkins, C. L. (2016) · Journal of Management · doi:10.1177/0149206315619011 · Cited by 163
Metadata
- Authors
- Andraszewicz, S., Scheibehenne, B., Rieskamp, J., Grasman, R., Verhagen, J., & Wagenmakers, E.-J.
- Venue
- Journal of Management
- Publisher
- SAGE Publications
- Published
- 2014-12-10
- Volume
- 41
- Issue
- 2
- Pages
- 521-543
- ISSN
- 0149-2063 (ISSN-L)
- 1557-1211
- OpenAlex
- W2105713027
- Cited by
- 344
- References
- 89
- FWCI
- 10.65
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Introduction to Bayesian Hypothesis Testing for Management Research. https://app.cochat.ai/papers/10.1177/0149206314560412
- The paper
- Andraszewicz, S., Scheibehenne, B., Rieskamp, J., Grasman, R., Verhagen, J., & Wagenmakers, E.-J. (2015). An Introduction to Bayesian Hypothesis Testing for Management Research. Journal of Management. https://doi.org/10.1177/0149206314560412
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
