A general model for testing mediation and moderation effects

Amanda J. Fairchild, David Mackinnon

Research output: Contribution to journalArticle

318 Citations (Scopus)

Abstract

This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example.

Original languageEnglish (US)
Pages (from-to)87-99
Number of pages13
JournalPrevention Science
Volume10
Issue number2
DOIs
StatePublished - Jun 2009

Fingerprint

Research
Datasets

Keywords

  • Indirect effect
  • Mediated moderation
  • Mediation
  • Moderated mediation
  • Moderation

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

Cite this

A general model for testing mediation and moderation effects. / Fairchild, Amanda J.; Mackinnon, David.

In: Prevention Science, Vol. 10, No. 2, 06.2009, p. 87-99.

Research output: Contribution to journalArticle

Fairchild, Amanda J. ; Mackinnon, David. / A general model for testing mediation and moderation effects. In: Prevention Science. 2009 ; Vol. 10, No. 2. pp. 87-99.
@article{f22b88afe0f149819007fe10a9606d79,
title = "A general model for testing mediation and moderation effects",
abstract = "This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example.",
keywords = "Indirect effect, Mediated moderation, Mediation, Moderated mediation, Moderation",
author = "Fairchild, {Amanda J.} and David Mackinnon",
year = "2009",
month = "6",
doi = "10.1007/s11121-008-0109-6",
language = "English (US)",
volume = "10",
pages = "87--99",
journal = "Prevention Science",
issn = "1389-4986",
publisher = "Springer New York",
number = "2",

}

TY - JOUR

T1 - A general model for testing mediation and moderation effects

AU - Fairchild, Amanda J.

AU - Mackinnon, David

PY - 2009/6

Y1 - 2009/6

N2 - This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example.

AB - This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example.

KW - Indirect effect

KW - Mediated moderation

KW - Mediation

KW - Moderated mediation

KW - Moderation

UR - http://www.scopus.com/inward/record.url?scp=67349216265&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=67349216265&partnerID=8YFLogxK

U2 - 10.1007/s11121-008-0109-6

DO - 10.1007/s11121-008-0109-6

M3 - Article

VL - 10

SP - 87

EP - 99

JO - Prevention Science

JF - Prevention Science

SN - 1389-4986

IS - 2

ER -