Cited by 56Advanced Causal Inference TechniquesStatistical Methods and Bayesian InferencePsychometric Methodologies and Testing

Mediation

Kenny, David A.·2014·Wiley StatsRef: Statistics Reference Online

Abstract

A mediator explains, at least in part, a causal relationship between two variables. The total relationship between the two variables is due to a indirect effect, that part explained by the mediator, and due to an direct effect, that part not explained be the mediator. Strong assumptions must be made to estimate and test mediation. The inclusion of multiple variables complicates mediational analysis. Mediational analysis while seemingly simple is actually quite complex.

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Crossref · 10.1002/9781118445112.stat06605

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Authors
Kenny, D. A.
Affiliations
University of Connecticut (US)
Corresponding author
Kenny, David A.
Venue
Wiley StatsRef: Statistics Reference Online
Publisher
Wiley
Published
2014-09-29
OpenAlex
W4240206238
Cited by
56
References
1
Citations by year
2026: 1 · 2025: 1 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 2 · 2019: 2 · 2018: 2 · 2017: 8 · 2016: 7 · 2015: 19 · 2014: 4
Type
other
Language
en
Open access
closed
Locations
Wiley eBooks (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Keywords
mediation analysis, indirect effects, direct effect, causal inference, multiple mediators

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