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Activity Number: 509 - Statistical Methodology
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #306953
Title: Causality and Intervention in the Context of Stochastic Differential Equation Models
Author(s): Paromita Banerjee* and Wojbor Woyczynski and Jeffrey M Albert
Companies: Case Western Reserve University and Case Western Reserve University and Case Western Reserve University
Keywords: Causality; Stochastic differential equations; Stochastic Intervention; Stochastic process; Tempered Stable Process; Structural equation model

To measure causal effect of realistic intervention, stochastic intervention can be considered as a significant mechanism. Estimating the causal effect of an intervention on a population typically involves defining parameters in a non-parametric structural equation model (SEM). We use Milstein scheme as model of causality to check whether postintervention stochastic differential equation (SDE) is the limit of postintervention SEM. This would also give a scope to compare Milstein method with the usual Euler method in terms of computational efficiency and convergence on SEM. We construct postintervention SDE using stable processes and tempered stable processes. The work finds its application in childhood dental care.

Authors who are presenting talks have a * after their name.

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