Results 21 to 30 of about 64,095 (292)
Causal mediation analysis with a latent mediator [PDF]
Biometrical Journal, 2015 Health researchers are often interested in assessing the direct effect of a treatment or exposure on an outcome variable, as well as its indirect (or mediation) effect through an intermediate variable (or mediator). For an outcome following a nonlinear model, the mediation formula may be used to estimate causally interpretable mediation effects.
Albert, Jeffrey M. +2 more
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Causal Mediation Analysis with Hidden Confounders [PDF]
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022 An important problem in causal inference is to break down the total effect of a treatment on an outcome into different causal pathways and to quantify the causal effect in each pathway. For instance, in causal fairness, the total effect of being a male employee (i.e., treatment) constitutes its direct effect on annual income (i.e., outcome) and the ...
Lu Cheng 0001 +2 more
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Journal of Causal Inference, 2022 Causal mediation analysis is complicated with multiple effect definitions that require different sets of assumptions for identification. This article provides a systematic explanation of such assumptions.
Nguyen Trang Quynh +3 more
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Causal mediation analysis with multiple causally non-ordered mediators [PDF]
Statistical Methods in Medical Research, 2015 In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation ...
Taguri, Masataka +2 more
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Semiparametric Estimation for Causal Mediation Analysis with Multiple Causally Ordered Mediators [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2021 AbstractCausal mediation analysis concerns the pathways through which a treatment affects an outcome. While most of the mediation literature focuses on settings with a single mediator, a flourishing line of research has examined settings involving multiple mediators, under which path-specific effects (PSEs) are often of interest. We consider estimation
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Causal Mediation Analysis for Stochastic Interventions [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2020 SummaryMediation analysis in causal inference has traditionally focused on binary exposures and deterministic interventions, and a decomposition of the average treatment effect in terms of direct and indirect effects. We present an analogous decomposition of the population intervention effect, defined through stochastic interventions on the exposure ...
Díaz, Iván, Hejazi, Nima
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Investigating potential mediator between statin and coronary artery calcification. [PDF]
PLoS ONE, 2018 Statins are mainstay anti-lipidaemic treatments for preventing cardiovascular diseases but also known to increase coronary artery calcification (CAC). However, underlying relationship between statin and CAC is still unclear.
Donghun Lee +3 more
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BayesGmed: An R-package for Bayesian causal mediation analysis.
PLoS ONE, 2023 BackgroundThe past decade has seen an explosion of research in causal mediation analysis. However, most analytic tools developed so far rely on frequentist methods which may not be robust in the case of small sample sizes.
Belay B Yimer +4 more
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A general approach to causal mediation analysis. [PDF]
Psychological Methods, 2010 Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the ...
Imai, Kosuke +2 more
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Continuous‐time causal mediation analysis
Statistics in Medicine, 2019 While causal mediation analysis has seen considerable recent development for a single measured mediator (M) and final outcome (Y), less attention has been given to repeatedly measured M and Y. Previous methods have typically involved discrete‐time models that limit inference to the particular measurement times used and do not recognize the continuous ...
Jeffrey M. Albert +4 more
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