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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...

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Detalles Bibliográficos
Autores principales: Fisher, Paige, Cao, Wentao, Yu, Qingzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
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.
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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
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