- An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages
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Sangmin Byeon, Woojoo Lee
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J Prev Med Public Health. 2023;56(4):303-311. Published online July 31, 2023
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DOI: https://doi.org/10.3961/jpmph.23.189
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 Abstract
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- 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.
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Summary
Korean summary
전통적 매개분석은 여러 유형의 변수 혹은 복잡한 상호작용을 포함할 경우, 직접 및 간접효과의 정의가 불분명하다는 비판에 직면해왔다. 이에 대한 대안으로서 인과매개분석은 반사실적 개념에 기반하여 직접 및 간접효과를 명료하게 정의하며 유연한 모델링을 가능하게 한다. 다만 이 새로운 접근의 주요 개념을 응용 연구자들이 이해하는 데에는 다소 어려운 측면이 있다. 이러한 점에서 이 논문에서는 중첩된 반사실적 변수에 기반한 인과적 모수의 정의를 상술하고 인과매개분석을 위한 대표적인 R 패키지인 medflex 및 mediation을 활용하여 공공 보건 사례에 대한 분석 실례 및 유의사항을 제공하였다.
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Citations
Citations to this article as recorded by  - Social class and moral judgment: a process dissociation perspective
Andreas Tutic, Friederike Haiser, Ivar Krumpal
Frontiers in Sociology.2024;[Epub] CrossRef
- Application of Standardization for Causal Inference in Observational Studies: A Step-by-step Tutorial for Analysis Using R Software
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Sangwon Lee, Woojoo Lee
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J Prev Med Public Health. 2022;55(2):116-124. Published online February 11, 2022
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DOI: https://doi.org/10.3961/jpmph.21.569
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Abstract
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PDFSupplementary Material
- Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.
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Summary
Korean summary
본 논문에서는 standardization 방법을 이용하여 risk difference, relative risk, risk ratio와 같은 인과성 효과를 R software을 이용하여 도출하는 튜토리얼을 제공합니다. 간암환자의 치료를 예시로, 합성 데이터를 이용한 치료제의 사망에 대한 인과적 효과를 탐색하는 튜토리얼을 제공합니다. 추가적으로, 인과성 관련 기본 이론을 집약적으로 설명하였고, standardization을 이용한 subgroup analysis 수행 방법이 제공됩니다.
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Citations
Citations to this article as recorded by - Homologous and Heterologous Prime-Boost Vaccination: Impact on Clinical Severity of SARS-CoV-2 Omicron Infection among Hospitalized COVID-19 Patients in Belgium
Marjan Meurisse, Lucy Catteau, Joris A. F. van Loenhout, Toon Braeye, Laurane De Mot, Ben Serrien, Koen Blot, Emilie Cauët, Herman Van Oyen, Lize Cuypers, Annie Robert, Nina Van Goethem
Vaccines.2023; 11(2): 378. CrossRef - Improved Clinical Outcomes With Early Anti-Tumour Necrosis Factor Alpha Therapy in Children With Newly Diagnosed Crohn’s Disease: Real-world Data from the International Prospective PIBD-SETQuality Inception Cohort Study
Renz C W Klomberg, Hella C van der Wal, Martine A Aardoom, Polychronis Kemos, Dimitris Rizopoulos, Frank M Ruemmele, Mohammed Charrout, Hankje C Escher, Nicholas M Croft, Lissy de Ridder, Ivan D Milovanovich, James J Ashton, Paul Henderson, Oren Ledder, T
Journal of Crohn's and Colitis.2023;[Epub] CrossRef
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