Statistical Inference for a Finite Population Mean with Machine Learning-Based Imputation for Missing Survey Data

Music City Center 

National statistical offices are increasingly using machine learning (ML) to improve survey estimates. ML methods help handle high-dimensional data and capture complex relationships, improving survey accuracy. In this presentation, we discuss a double/debiased ML framework for handling item nonresponse while ensuring valid statistical inference with ML-based imputation. We also present theoretical and simulation results that illustrate the framework's effectiveness across different scenarios.

Imputation

Item nonresponse

Machine learning

Variance estimation

Doubly robust estimator

Calibrated imputation