Abstract #302036

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JSM 2003 Abstract #302036
Activity Number: 179
Type: Contributed
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #302036
Title: Structural Modeling of Random Effects of Observed Exposures in Randomized Experiments
Author(s): Els Goetghebeur*+ and Stijn Vansteelandt
Companies: University of Ghent and Ghent University
Address: TWI - Krijgslaan 281-S9, B-9000 Gent, , , Belgium
Keywords: noncompliance ; random effects ; structural modeling ; causal inference
Abstract:

Semiparametric structural mean and distribution models are popular for analyzing the effect of observed exposures in randomized experiments.They model exposure-specific contrasts between observed and potential treatment-free outcomes. The latter impose more severe restrictions than the former. We consider a middle road and model structural means and covariances jointly. This is useful when outcomes are vectors, as with cluster randomization or repeated outcomes. It enables estimation of structural interaction effects with latent (treatment-free) outcomes while inference uses randomization to protect the null hypothesis. We thus consider random effects structural nested mean models versus structural nested mean and covariance models for continuous outcomes. The former run into problems, the latter allow to estimate average structural effects and variation in structural effects over individuals, without specifying the random structural effects distribution. Besides the usual set of estimating equations we solve a set involving second order moments of observed and latent outcomes. Asymptotic efficiency and finite sample properties are explored.

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