IOE EPrints

Mediation analysis with intermediate confounding : structural equation modeling viewed through the causal inference lens

De Stavola, Bianca L and Daniel, Rhian M and Ploubidis, George B and Micali, Nadia (2015) Mediation analysis with intermediate confounding : structural equation modeling viewed through the causal inference lens. American Journal of Epidemiology, 181 (1). pp. 64-80. ISSN 1476-6256. DOI UNSPECIFIED

Full text not available from this repository.
SFX image for help Not from UCL IOE? image for help

Abstract

The study of mediation has a long tradition in the social sciences and a relatively more recent one in epidemiology. The first school is linked to path analysis and structural equation models (SEMs), while the second is related mostly to methods developed within the potential outcomes approach to causal inference. By giving model-free definitions of direct and indirect effects and clear assumptions for their identification, the latter school has formalized notions intuitively developed in the former and has greatly increased the flexibility of the models involved. However, through its predominant focus on nonparametric identification, the causal inference approach to effect decomposition via natural effects is limited to settings that exclude intermediate confounders. Such confounders are naturally dealt with (albeit with the caveats of informality and modeling inflexibility) in the SEM framework. Therefore, it seems pertinent to revisit SEMs with intermediate confounders, armed with the formal definitions and (parametric) identification assumptions from causal inference. Here we investigate: 1) how identification assumptions affect the specification of SEMs, 2) whether the more restrictive SEM assumptions can be relaxed, and 3) whether existing sensitivity analyses can be extended to this setting. Data from the Avon Longitudinal Study of Parents and Children (1990-2005) are used for illustration.

Item Type: Article
Additional Information: © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.
Depositing User: Atira Pure
Date Deposited: 29 Jan 2015 09:17
Last Modified: 29 Jan 2015 09:17
View Item View Item