Doubly robust integration of nonprobability and probability survey data

Fuente: arXiv
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Autori principali: Seaman, Shaun R, Nyberg, Tommy, Presanis, Anne M
Natura: Preprint
Pubblicazione: 2025
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author Seaman, Shaun R
Nyberg, Tommy
Presanis, Anne M
author_facet Seaman, Shaun R
Nyberg, Tommy
Presanis, Anne M
contents Doubly robust estimators combine an inverse probability weighting estimator and a mass imputation estimator. Several doubly robust estimators for estimating the population mean (or prevalence) of an outcome have been proposed for integrating outcome and covariate data from a nonprobability survey with covariate data from an auxiliary probability survey. However, the question of how to combine a doubly robust estimate with a corresponding estimate based on outcome data from the auxiliary probability survey alone has only received limited attention. In this paper, we (i) review previously proposed doubly robust estimators, (ii) provide formulae for the variance of doubly robust estimators and the covariance between doubly robust and probability survey estimates, (iii) propose a framework for how to combine efficiently a doubly robust estimate from a nonprobability sample with an estimate based on the auxiliary probability sample alone, and (iv) provide formulae for the variance of such combined estimates.
format Preprint
id arxiv_https___arxiv_org_abs_2508_05859
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Doubly robust integration of nonprobability and probability survey data
Seaman, Shaun R
Nyberg, Tommy
Presanis, Anne M
Methodology
62F10, 62F12
G.3
Doubly robust estimators combine an inverse probability weighting estimator and a mass imputation estimator. Several doubly robust estimators for estimating the population mean (or prevalence) of an outcome have been proposed for integrating outcome and covariate data from a nonprobability survey with covariate data from an auxiliary probability survey. However, the question of how to combine a doubly robust estimate with a corresponding estimate based on outcome data from the auxiliary probability survey alone has only received limited attention. In this paper, we (i) review previously proposed doubly robust estimators, (ii) provide formulae for the variance of doubly robust estimators and the covariance between doubly robust and probability survey estimates, (iii) propose a framework for how to combine efficiently a doubly robust estimate from a nonprobability sample with an estimate based on the auxiliary probability sample alone, and (iv) provide formulae for the variance of such combined estimates.
title Doubly robust integration of nonprobability and probability survey data
topic Methodology
62F10, 62F12
G.3
url https://arxiv.org/abs/2508.05859