Equivalence of the Mediation, Confounding and Suppression Effect

By David P. MacKinnon, J. Krull, C. Lockwood. Prevention Science, 2000

3,997 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/eb826f7db64a07a4eb83df4794da9999007c7e35

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In Management Science and Operations Research

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Citations in the corpus

Psychological Functioning in a Sample of Long-Term Practitioners of Mindfulness Meditation (2009, methodology): “We used a t test described by MacKinnon, Krull, and Lockwood (2000) for testing the significance of the reduction in this coefficient when the mediator is included in the model.”
Driving factors of innovation in family and non-family SMEs (2018, background): “ly significant total effect is not obligatory to observe mediation effects because suppressor effects may be at work (Kenny et al. 1998; MacKinnon et al. 2000).”
Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium (2009, background): “Y, and those paths operate in opposite directions (cf., MacKinnon et al., 2000 ).”
A model for the effects of job insecurity on performance, turnover intention, and absenteeism (2010, background): “For suppressor models, therefore, the correlation between the independent and the dependent variable does not have to be statistically significant (MacKinnon et al., 2000; Shrout & Bolger, 2002).”
The ambivalence of challenge stressors: Time pressure associated with both negative and positive well-being (2012, methodology): “The analytic methods for testing suppression are the same as for mediation (Cheung & Lau, 2008; MacKinnon et al., 2000; Rucker et al., 2011), that is, the test of significance of an indirect effect (a×b).”
Focus on opportunities as a mediator of the relationships between age, job complexity, and work performance (2010, neutral): “…to these critics, if the mediating process is rather distant or complex (as in the age-performance relationship), the magnitude of the relationship between X and Y becomes smaller due to additional or competing factors in the mediating process (MacKinnon et al., 2000, 2002; Shrout & Bolger, 2002).”
Trust Between Entrepreneurs and Angel Investors (2014, background): “However, when direct and indirect effects are opposite in sign—as is the case here—the relationship between the dependent and independent variable may actually increase rather than diminish when controlling for the mediator (MacKinnon et al., 2000).”
SPSS and SAS procedures for estimating indirect effects in simple mediation models (2004, background): “MacKinnon, Krull, and Lockwood (2000) have demonstrated that mediation, suppression, and confounding effects are mathematically equivalent, although they are assessed by looking for different patterns of relationships among variables.”
Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis (2010, neutral): “Other authors have referred to complementary mediations as “consistent” models or “positive confounding” and to competitive mediations as “inconsistent” models or “negative confounding” (Cliff and Earleywine 1994; Collins et al. 1998; Davis 1985; MacKinnon et al. 2000; McFatter 1979; Shrout and Bolg”