Causal Effects in Mediation Modeling: An Introduction With Applications to Latent Variables
Abstract
Causal inference in mediation analysis offers counterfactually based causal definitions of direct and indirect effects, drawing on research by Robins, Greenland, Pearl, VanderWeele, Vansteelandt, Imai, and others. This type of mediation effect estimation is little known and seldom used among analysts using structural equation modeling (SEM). The aim of this article is to describe the new analysis opportunities in a way that is accessible to SEM...
Paper Details
Title
Causal Effects in Mediation Modeling: An Introduction With Applications to Latent Variables
Published Date
Jan 2, 2015
Journal
Volume
22
Issue
1
Pages
12 - 23
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