Cargando…
An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages
Traditional mediation analysis, which relies on linear regression models, has faced criticism due to its limited suitability for cases involving different types of variables and complex covariates, such as interactions. This can result in unclear definitions of direct and indirect effects. As an alt...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Preventive Medicine
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415648/ https://www.ncbi.nlm.nih.gov/pubmed/37551068 http://dx.doi.org/10.3961/jpmph.23.189 |
_version_ | 1785087590905413632 |
---|---|
author | Byeon, Sangmin Lee, Woojoo |
author_facet | Byeon, Sangmin Lee, Woojoo |
author_sort | Byeon, Sangmin |
collection | PubMed |
description | Traditional mediation analysis, which relies on linear regression models, has faced criticism due to its limited suitability for cases involving different types of variables and complex covariates, such as interactions. This can result in unclear definitions of direct and indirect effects. As an alternative, causal mediation analysis using the counterfactual framework has been introduced to provide clearer definitions of direct and indirect effects while allowing for more flexible modeling methods. However, the conceptual understanding of this approach based on the counterfactual framework remains challenging for applied researchers. To address this issue, the present article was written to highlight and illustrate the definitions of causal estimands, including controlled direct effect, natural direct effect, and natural indirect effect, based on the key concept of nested counterfactuals. Furthermore, we recommend using 2 R packages, ‘medflex’ and ‘mediation’, to perform causal mediation analysis and provide public health examples. The article also offers caveats and guidelines for accurate interpretation of the results. |
format | Online Article Text |
id | pubmed-10415648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Korean Society for Preventive Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-104156482023-08-12 An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages Byeon, Sangmin Lee, Woojoo J Prev Med Public Health Special Article Traditional mediation analysis, which relies on linear regression models, has faced criticism due to its limited suitability for cases involving different types of variables and complex covariates, such as interactions. This can result in unclear definitions of direct and indirect effects. As an alternative, causal mediation analysis using the counterfactual framework has been introduced to provide clearer definitions of direct and indirect effects while allowing for more flexible modeling methods. However, the conceptual understanding of this approach based on the counterfactual framework remains challenging for applied researchers. To address this issue, the present article was written to highlight and illustrate the definitions of causal estimands, including controlled direct effect, natural direct effect, and natural indirect effect, based on the key concept of nested counterfactuals. Furthermore, we recommend using 2 R packages, ‘medflex’ and ‘mediation’, to perform causal mediation analysis and provide public health examples. The article also offers caveats and guidelines for accurate interpretation of the results. Korean Society for Preventive Medicine 2023-07 2023-07-31 /pmc/articles/PMC10415648/ /pubmed/37551068 http://dx.doi.org/10.3961/jpmph.23.189 Text en Copyright © 2023 The Korean Society for Preventive Medicine https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Special Article Byeon, Sangmin Lee, Woojoo An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages |
title | An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages |
title_full | An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages |
title_fullStr | An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages |
title_full_unstemmed | An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages |
title_short | An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages |
title_sort | introduction to causal mediation analysis with a comparison of 2 r packages |
topic | Special Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415648/ https://www.ncbi.nlm.nih.gov/pubmed/37551068 http://dx.doi.org/10.3961/jpmph.23.189 |
work_keys_str_mv | AT byeonsangmin anintroductiontocausalmediationanalysiswithacomparisonof2rpackages AT leewoojoo anintroductiontocausalmediationanalysiswithacomparisonof2rpackages AT byeonsangmin introductiontocausalmediationanalysiswithacomparisonof2rpackages AT leewoojoo introductiontocausalmediationanalysiswithacomparisonof2rpackages |