Riesz representers for the rest of us

TL;DR

This paper introduces the Riesz representation theorem to epidemiologists, explaining its relevance and utility in semiparametric efficient estimation and Riesz regression through clear examples.

Contribution

It provides an accessible explanation of the Riesz representation theorem and demonstrates its application in epidemiology and causal inference.

Findings

Clarifies the Riesz representation theorem for epidemiologists

Demonstrates the use of Riesz regression in causal inference

Provides step-by-step worked examples

Abstract

The application of semiparametric efficient estimators, particularly those that leverage machine learning, is rapidly expanding within epidemiology and causal inference. This literature is increasingly invoking the Riesz representation theorem and Riesz regression. This paper aims to introduce the Riesz representation theorem to an epidemiologic audience, explaining what it is and why it's useful, using step-by-step worked examples.