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Activity Number: 629 - The Impacts of Measurement Error in Scientific Discoveries
Type: Invited
Date/Time: Thursday, August 1, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #300356
Title: Weighted Causal Inference Methods with Misclassified Outcomes
Author(s): Grace Yi*
Companies: University of Waterloo
Keywords: causal inference; misclassification ; average treatment effect; inverse probability weighted method

Inverse probability weighting (IPW) estimation has been popularly used to consistently estimate the average treatment effect (ATE). Its validity, however, is challenged by the presence of error-prone variables. In application, measurement error is ubiquitously present in data collection due to various reasons. Naively ignoring measurement error effects usually yields biased inference results. In this talk, I will discuss the IPW estimation with mismeasured outcome variables. The impact of measurement error for both continuous and discrete outcome variables will be examined. I will describe estimation procedures with the outcome misclassification effects accommodated. Consistency and efficiency will be investigated. Numerical studies will be reported to assess the performance of the proposed methods.

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

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