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Cited by 273

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Analysis of Mediating Variables in Prevention and Intervention Research: (495892006-009)

MacKinnon, David P., US Department of Health and Human Services; National Institute on Drug Abuse·1994·PsycEXTRA Dataset

Abstract

Mediational analysis is one way to test specific hypotheses derived from theory. Although this analysis has been suggested in the prevention literature, mediation analysis rarely is conducted. As the field of prevention matures, more questions about how prevention programs work (or fail to work) will emerge. Studies of mediation can address these questions, thereby reducing the cost and enhancing the impact of prevention programs. The methods outlined here can be applied in the evaluation of primary, secondary, and tertiary prevention programs. Since most prevention studies include measurement of some mediating constructs, mediation effects can be assessed on many existing data sets. Mediation analysis can be used to test ideas about prevention.

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Metadata

Authors
MacKinnon, D. P., & US Department of Health and Human Services; National Institute on Drug Abuse
Venue
PsycEXTRA Dataset
Published
1994
Volume
139
Pages
127-53
OpenAlex
W1545938406
Cited by
273
References
39
Type
dataset
Language
en
Open access
closed

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CoChat. (2026). Citation check: Analysis of Mediating Variables in Prevention and Intervention Research: (495892006-009). https://app.cochat.ai/papers/10.1037/e495892006-009
The paper
MacKinnon, D. P., & US Department of Health and Human Services; National Institute on Drug Abuse. (1994). Analysis of Mediating Variables in Prevention and Intervention Research: (495892006-009). PsycEXTRA Dataset. https://doi.org/10.1037/e495892006-009

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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.