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Activity Number: 69
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract #320613
Title: Nonlinear Structural Equation Models in Environmental Epidemiology
Author(s): Esben Budtz-Jørgensen*
Keywords: latent variable ; non-linear ; robust ; mis-specification

Structural equation models (SEMs) have been shown to be powerful for drawing causal inference in high dimensional data. In the measurement part of the model, observed variables are linked to a limited number of latent variables which are then related to each other in a structural model. The classical SEM builds on strong linearity assumptions. This is a serious limitation in applications which will often require in the introduction of non-linear terms. This paper considers methods for estimating and identifying non-linear associations in the SEM framework. Methods are illustrated in epidemiological data on health effects of prenatal mercury exposure.

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