The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Bayesian mediation analysis.
Open accessAbstract
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian mediation analysis, inference is straightforward and exact, which makes it appealing for studies with small samples. Third, the Bayesian approach is conceptually simpler for multilevel mediation analysis. Simulation studies and analysis of 2 data sets are used to illustrate the proposed methods. (PsycINFO Database Record (c) 2009 APA, all rights reserved).
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
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models
Sobel, M. E. (1982) · Sociological Methodology · doi:10.2307/270723 · Cited by 12,810
Mediation in experimental and nonexperimental studies: New procedures and recommendations.
Shrout, P. E., & Bolger, N. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.4.422 · Cited by 11,335
A comparison of methods to test mediation and other intervening variable effects
MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.83 · Cited by 9,406
Self-citationConfidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods
MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr3901_4 · Cited by 7,806
Self-citationGeneral methods for monitoring convergence of iterative simulations
Brooks, S. P., & Gelman, A. (1998) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1998.10474787 · Cited by 6,045
Introduction to Statistical Mediation Analysis
MacKinnon, D. P. (2012) · doi:10.4324/9780203809556 · Cited by 5,618
Self-citationEquivalence of the Mediation, Confounding and Suppression Effect
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000) · Prevention Science · doi:10.1023/a:1026595011371 · Cited by 4,188
Self-citationMediators and Moderators of Treatment Effects in Randomized Clinical Trials
Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002) · Archives of General Psychiatry · doi:10.1001/archpsyc.59.10.877 · Cited by 2,562
Cited by
An index and test of linear moderated mediation
Hayes, A. F. (2015) · Multivariate Behavioral Research · doi:10.1080/00273171.2014.962683 · Cited by 3,979
Hayes, A. F. (2018) · Communication Monographs · doi:10.1080/03637751.2017.1352100 · Cited by 3,516
Hayes, A. F., & Rockwood, N. J. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.11.001 · Cited by 2,350
Using 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
Advantages of Monte Carlo confidence intervals for indirect effects
Preacher, K. J., & Selig, J. P. (2012) · Communication Methods and Measures · doi:10.1080/19312458.2012.679848 · Cited by 1,908
Metadata
- Authors
- Yuan, Y., & MacKinnon, D. P.
- Venue
- Psychological Methods
- Published
- 2009-12
- Volume
- 14
- Issue
- 4
- Pages
- 301-322
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2008992734
- Cited by
- 637
- References
- 13
- FWCI
- 6.83
- 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: Bayesian mediation analysis. https://app.cochat.ai/papers/10.1037/a0016972
- The paper
- Yuan, Y., & MacKinnon, D. P. (2009). Bayesian mediation analysis. Psychological Methods. https://doi.org/10.1037/a0016972
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.