Survey Design and Estimating Equations when Combining Big Data with Probability Samples

TL;DR

This paper develops a unified method to combine big data with probability samples, producing estimators that are consistent, unbiased, and more efficient, addressing selection bias in official statistics.

Contribution

It introduces a novel estimating equation framework that integrates big data with probability sampling, ensuring valid inference under weak assumptions.

Findings

Integrated estimators are consistent and asymptotically unbiased.

Variance estimators are derived for both design-based and superpopulation-based inference.

Combining big data with probability samples improves efficiency when dependence is low and population is large.

Abstract

The use of big data in official statistics and the applied sciences is accelerating, but statistics computed using only big data often suffer from substantial selection bias. This leads to inaccurate estimation and invalid statistical inference. We rectify the issue for a broad class of linear and nonlinear statistics by producing estimating equations that combine big data with a probability sample. Under weak assumptions about an unknown superpopulation, we show that our integrated estimator is consistent and asymptotically unbiased with an asymptotic normal distribution. Variance estimators with respect to both the sampling design alone and jointly with the superpopulation are obtained at once using a single, unified theoretical approach. A surprising corollary is that strategies minimising the design variance almost minimise the joint variance when the population and sample sizes are large. The integrated estimator is shown to be more efficient than its survey-only counterpart if dependence between sample membership indicators is small and the finite population is large. We illustrate our method for quantiles, the Gini index, linear regression coefficients and maximum likelihood estimators where the sampling design is stratified simple random sampling without replacement. Our results are illustrated in a simulation of individual Australian incomes.