[Statlist] Friday, December 15, 2017 with Preetam Nandy, University of Pennsylvania

Kaiser-Heinzmann Susanne @u@@nne@k@|@er @end|ng |rom @t@t@m@th@ethz@ch
Tue Dec 12 13:16:27 CET 2017


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ETH and University of Zurich

Organisers:

Proff. P. Bühlmann - L. Held - T. Hothorn - M. Maathuis -
N. Meinshausen - S. van de Geer - M. Wolf

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We are glad to announce the following talk:

Friday, December 15, 2017 at 11:15pm, ETH Zurich, HG G19.1
with Preetam Nandy, University of Pennsylvania

Title:

Estimating and testing individual mediation effects in high-dimensional settings 

Abstract:

We consider the problem of identifying intermediate variables (or mediators) that regulate the effect of a treatment on an outcome. While there has been significant research on this topic, little work has been done when the set of potential mediators is high-dimensional. A further complication arises when the potential mediators are interrelated. In particular, we assume that the causal structure of the treatment, potential mediators and outcome is a directed acyclic graph. In this setting, we propose novel methods for estimating and testing the influence of a mediator on the outcome for high-dimensional linear structural equation models (linear SEMs). For the estimation of individual mediation effect, we propose a modification of the IDA algorithm that was developed for estimating causal effects from observational data. While most of the approaches for estimating the influence of potential mediators ignore the causal relationship among the mediators, our IDA-based approach estimates the underlying causal graph from data. We derive a high-dimensional consistency result for the IDA-based estimators when the data are generated from a linear SEM with sub-Gaussian errors. Further, we propose a first asymptotically valid testing framework in such a setting, leading to a principled FDR control approach for the identification of the set of true mediators. Finally, we empirically demonstrate the importance of using an estimated causal graph in high-dimensional mediation analysis.

This abstract is also to be found under the following link: http://stat.ethz.ch/events/research_seminar

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