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Using SAS Macros for Multiple Mediation Analysis in R
Mediation analysis refers to the process of making inferences on effects of third variables that intervene in the relationship between an exposure and response variable. The relationships among variables can be modelled by generalized linear models (GLM). However, GLM are not sufficient to describe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336624/ https://www.ncbi.nlm.nih.gov/pubmed/34354832 http://dx.doi.org/10.5334/jors.277 |
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author | Fisher, Paige Cao, Wentao Yu, Qingzhao |
author_facet | Fisher, Paige Cao, Wentao Yu, Qingzhao |
author_sort | Fisher, Paige |
collection | PubMed |
description | Mediation analysis refers to the process of making inferences on effects of third variables that intervene in the relationship between an exposure and response variable. The relationships among variables can be modelled by generalized linear models (GLM). However, GLM are not sufficient to describe relationships among variables when there are nonlinear relationships and potential interaction effects. A general mediation analysis method was developed using not only GLMs, but also multiple additive regression trees and smoothing splines by Yu and Li (2017). The method is implemented in the R package, mma. In this paper, we developed SAS macros so that functions in the mma package can be called and the mediation analysis performed in the SAS environment. |
format | Online Article Text |
id | pubmed-8336624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-83366242021-08-04 Using SAS Macros for Multiple Mediation Analysis in R Fisher, Paige Cao, Wentao Yu, Qingzhao J Open Res Softw Article Mediation analysis refers to the process of making inferences on effects of third variables that intervene in the relationship between an exposure and response variable. The relationships among variables can be modelled by generalized linear models (GLM). However, GLM are not sufficient to describe relationships among variables when there are nonlinear relationships and potential interaction effects. A general mediation analysis method was developed using not only GLMs, but also multiple additive regression trees and smoothing splines by Yu and Li (2017). The method is implemented in the R package, mma. In this paper, we developed SAS macros so that functions in the mma package can be called and the mediation analysis performed in the SAS environment. 2020-10-07 2020 /pmc/articles/PMC8336624/ /pubmed/34354832 http://dx.doi.org/10.5334/jors.277 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Fisher, Paige Cao, Wentao Yu, Qingzhao Using SAS Macros for Multiple Mediation Analysis in R |
title | Using SAS Macros for Multiple Mediation Analysis in R |
title_full | Using SAS Macros for Multiple Mediation Analysis in R |
title_fullStr | Using SAS Macros for Multiple Mediation Analysis in R |
title_full_unstemmed | Using SAS Macros for Multiple Mediation Analysis in R |
title_short | Using SAS Macros for Multiple Mediation Analysis in R |
title_sort | using sas macros for multiple mediation analysis in r |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336624/ https://www.ncbi.nlm.nih.gov/pubmed/34354832 http://dx.doi.org/10.5334/jors.277 |
work_keys_str_mv | AT fisherpaige usingsasmacrosformultiplemediationanalysisinr AT caowentao usingsasmacrosformultiplemediationanalysisinr AT yuqingzhao usingsasmacrosformultiplemediationanalysisinr |