Title

An Efficient Computational Method for Causal Inference in High-Dimensional Data: Neighborhood-Based Cross Fitting

Authors

David Agboola

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Document Type

Presentation

Publication Date

2-22-2022

Abstract

About My Research: Current method suggests splitting data at least a thousand times to get reliable results. This is computationally expensive, especially for high-dimensional data (that is, data with a large number of variables relative to the sample size). I am using the structure of data as a shortcut for splitting; thus, the data is only required to be split twice. My method is ten times faster and achieves the same result as splitting the data a thousand times.

Why I’m participating in the 3MT: I'm participating in the 3MT event to communicate my research findings to the public. Specifically, to communicate my research to content experts who would find my method applicable to their research.

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