Results 261 to 270 of about 64,095 (292)

Exploring the role of blood pressure in the black-white disparity in cardiovascular disease mortality: a causal mediation analysis. [PDF]

J Epidemiol Community Health
Zhao F, Gidwani R, Wang MC, Chen L, Nianogo RA.   +4 more
europepmc   +1 more source

Investigating the Mechanisms of Reduced Blood Transfusions after Delayed Umbilical Cord Clamping: The TITANS Causal Mediation Analysis.

Neonatology
Libesman S, Seidler AL, Tan-Koay AG, Cunningham PS, Robledo K, Cruise S, Wadsworth M, Kluckow M, Gill AW, de Waal K, Tarnow-Mordi W, Liley HG.   +11 more
europepmc   +1 more source

Causal Mediation Analysis

This two-day seminar provides a comprehensive exploration of causal mediation analysis, emphasizing strong theoretical foundations and practical applications for researchers in diverse fields. Participants will gain crucial skills in implementing these advanced methodologies using R and Stata, enhancing the credibility and impact of their research ...
Paola Zaninotto, Martin Danka
core   +4 more sources

Statistical Mediation Analysis for Models with a Binary Mediator and a Binary Outcome: the Differences Between Causal and Traditional Mediation Analysis

Prevention Science, 2021
Mediation analysis is an important statistical method in prevention research, as it can be used to determine effective intervention components. Traditional mediation analysis defines direct and indirect effects in terms of linear regression coefficients.
Judith J M Rijnhart, Matthew J Valente, Heather L Smyth   +2 more
exaly   +2 more sources

Meaningful Mediation Analysis: Plausible Causal Inference and Informative Communication

Journal of Consumer Research, 2017
Statistical mediation analysis has become the technique of choice in consumer research to make causal inferences about the influence of a treatment on an outcome via one or more mediators.
Rik Pieters
exaly   +2 more sources

IDENTIFYING MECHANISMS BEHIND POLICY INTERVENTIONS VIA CAUSAL MEDIATION ANALYSIS [PDF]

Journal of Policy Analysis and Management, 2015
Causal analysis in program evaluation has primarily focused on the question about whether or not a program, or package of policies, has an impact on the targeted outcome of interest.
Luke Keele, Dustin Tingley, Teppei Yamamoto   +2 more
exaly   +2 more sources

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Causal mediation analysis with latent subgroups

Statistics in Medicine, 2021
In biomedical studies, the causal mediation effect might be heterogeneous across individuals in the study population due to each study subject's unique characteristics. While individuals' mediation effects may differ from each other, it is often reasonable and more interpretable to assume that individuals belong to several distinct latent subgroups ...
WenWu Wang, Jinfeng Xu, Joel Schwartz, Andrea Baccarelli, Zhonghua Liu   +4 more
openaire   +3 more sources

Causal Mediation Analysis with Multiple Time-varying Mediators

Epidemiology, 2022
In longitudinal studies with time-varying exposures and mediators, the mediational g-formula is an important method for the assessment of direct and indirect effects. However, current methodologies based on the mediational g-formula can deal with only one mediator. This limitation makes these methodologies inapplicable to many scenarios.
Tai, An-Shun, Lin, Sheng-Hsuan, Chu, Yu-Cheng, Yu, Tsung, Puhan, Milo A, VanderWeele, Tyler   +5 more
openaire   +2 more sources

Causal Mediation Analysis

American Journal of Evaluation, 2015
In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no “gold standard” method for the identification of causal mediation effects.
openaire   +1 more source