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Mediation analysis for logistic regression with interactions: Application of a surrogate marker in ophthalmology

Mediation analysis is often based on fitting two models, one including and another excluding a potential mediator, and subsequently quantify the mediated effects by combining parameter estimates from these two models. Standard errors of such derived parameters may be approximated using the delta met...

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Detalles Bibliográficos
Autores principales: Jensen, Signe M., Hauger, Hanne, Ritz, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5809055/
https://www.ncbi.nlm.nih.gov/pubmed/29432493
http://dx.doi.org/10.1371/journal.pone.0192857
Descripción
Sumario:Mediation analysis is often based on fitting two models, one including and another excluding a potential mediator, and subsequently quantify the mediated effects by combining parameter estimates from these two models. Standard errors of such derived parameters may be approximated using the delta method. For a study evaluating a treatment effect on visual acuity, a binary outcome, we demonstrate how mediation analysis may conveniently be carried out by means of marginally fitted logistic regression models in combination with the delta method. Several metrics of mediation are estimated and results are compared to findings using existing methods.