The DOI matches its Crossref record; 49 of the 52 references it cites were found in a registry or an index.
Equivalence of the Mediation, Confounding and Suppression Effect
Open accessAbstract
This paper describes the statistical similarities among mediation, confounding, and suppression. Each is quantified by measuring the change in the relationship between an independent and a dependent variable after adding a third variable to the analysis. Mediation and confounding are identical statistically and can be distinguished only on conceptual grounds. Methods to determine the confidence intervals for confounding and suppression effects are proposed based on methods developed for mediated effects. Although the statistical estimation of effects and standard errors is the same, there are important conceptual differences among the three types of effects.
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“As has been recommended (see MacKinnon, Krull, & Lockwood, 2000; Preacher & Hayes, 2008), the multiple mediation analysis was accompanied by simple mediation analyses to bypass the issues that suppression effects can obscure possible indirect effects of individual mediators.”
From Change in Decentering Mediates Improvement in Anxiety in Mindfulness-Based Stress Reduction for Generalized Anxiety Disorder (2015) · cites this paper as MacKinnon, Krull, & Lockwood, 2000
In the citing paper
“The change from minus to plus on the effect of time on pain interference when psychological inflexibility was entered into the model makes the interpretation more unclear, but according to both Kenny et al. and MacKinnon et al. (59,60) this change in direction of effect can also be a sign of inconsistent mediation or a negative suppressor variable.”
From Internet-delivered acceptance and commitment therapy (iACT) for chronic pain—feasibility and preliminary effects in clinical and self-referred patients (2020) · cites this paper as [59]
In the citing paper
“In statistical terms, the pattern of relations depicted in Figure 1 amounts to inconsistent mediation (MacKinnon et al., 2000). This occurs when the direct effect of a predictor (here, an adverse event) is directionally opposite to its indirect effect via a mediator (nostalgia).”
From Water From the Lake of Memory: The Regulatory Model of Nostalgia (2023) · cites this paper as MacKinnon et al., 2000
In the citing paper
“However, the most theoretically noteworthy result was the positive direct association between FoMO and psychological well-being, shown through a suppressor effect (i.e. when a variable masks the true association between two constructs due to statistical suppression; MacKinnon et al., 2000).”
From Fear of missing out and psychological well-being: Examining the dual pathways of problematic social media use and digital burnout (2026) · cites this paper as MacKinnon et al., 2000
In the citing paper
“However, the most theoretically noteworthy result was the positive direct association between FoMO and psychological well-being, shown through a suppressor effect (i.e. when a variable masks the true association between two constructs due to statistical suppression; MacKinnon et al., 2000).”
From Fear of missing out and psychological well-being: Examining the dual pathways of problematic social media use and digital burnout (2026) · cites this paper as MacKinnon et al., 2000
In the citing paper
“The indirect effects of trust on reliance behaviours are small and opposite to the direct effects, indicating a suppression model (MacKinnon et al., 2000).”
From The role of critical thinking on undergraduates' reliance behaviours on generative AI in problem‐solving (2025) · cites this paper as MacKinnon et al., 2000
In the citing paper
“We will assess the significance of the direct effect (coefficient c2 in eq. 3): statistical significance of this term will signify that mediation by M is partial [206, 207].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [206]
In the citing paper
“Associations between an outcome and a set of inputs could have occurred by chance, owing to a confounding factor or a biased data set.”
From Applications of machine learning in animal behaviour studies (2017) · cites this paper as MacKinnon, Krull, & Lockwood, 2000
In the citing paper
“Further analysis revealed that the low bivariate correlations combined with greater weights in the SEM likely reflected a suppressor effect [34], [35].”
From The Role of Conspiracist Ideation and Worldviews in Predicting Rejection of Science (2013) · cites this paper as [34]
In the citing paper
“Considering the null correlation between PSE and positive affect, PSE acted as a suppressor variable in the relationship between RSE and positive affect [47].”
From Self-esteem and subjective well-being revisited: The roles of personal, relational, and collective self-esteem (2017) · cites this paper as [47]
In the citing paper
“One solution is to simply use the mediated fraction [224], which is statistically identical to the confounded fraction above but simply assumes that the third variable is a mediator, rather than confounder [225].”
From Personality and Longevity: Knowns, Unknowns, and Implications for Public Health and Personalized Medicine (2011) · cites this paper as [225]
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Metadata
- Authors
- MacKinnon, D. P., Krull, J. L., & Lockwood, C. M.
- Affiliations
- Arizona State University (US)
- Corresponding author
- MacKinnon, David P.
- ORCID
- MacKinnon, David P.
- Venue
- Prevention Science
- Published
- 2000-12
- Volume
- 1
- Issue
- 4
- Pages
- 173-181
- ISSN
- 1389-4986 (ISSN-L)
- 1573-6695
- PMC
- PMC2819361
- OpenAlex
- W1715619412
- Cited by
- 4,188
- References
- 52
- Citations by year
- 2026: 403 · 2025: 291 · 2024: 253 · 2023: 278 · 2022: 306 · 2021: 271 · 2020: 275 · 2019: 210 · 2018: 205 · 2017: 190 · 2016: 197 · 2015: 166 · 2014: 215 · 2013: 167 · 2012: 169
- FWCI
- 8.35
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Prevention Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Drug Abuse (DA 09757, R01DA009757, R37DA009757)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- mediation, confounding, suppression effect, third variable, causal inference, confidence intervals, standard errors, effect estimation
- MeSH terms
- Data Interpretation, Statistical, Humans, Reproducibility of Results, Models, Statistical, Bias, Causality, Confounding Factors, Epidemiologic, Effect Modifier, Epidemiologic, Confidence Intervals, Least-Squares Analysis
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 ›
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