Local polynomial regression for pooled response data

TL;DR

This paper introduces local polynomial estimators for the conditional mean in pooled response data, analyzing their asymptotic properties, finite sample performance, and practical applications across different pooling designs.

Contribution

It develops novel local polynomial estimators tailored for pooled response data and thoroughly evaluates their theoretical properties and practical performance.

Findings

Estimators have desirable asymptotic properties.

Simulation studies show good finite sample performance.

Applications demonstrate practical utility in real data scenarios.

Abstract

We propose local polynomial estimators for the conditional mean of a continuous response when only pooled response data are collected under different pooling designs. Asymptotic properties of these estimators are investigated and compared. Extensive simulation studies are carried out to compare finite sample performance of the proposed estimators under various model settings and pooling strategies. We apply the proposed local polynomial regression methods to two real-life applications to illustrate practical implementation and performance of the estimators for the mean function.