#2157. Combining non-probability and probability survey samples through mass imputation

July 2026publication date
Proposal available till 30-05-2025
5 total number of authors per manuscript6020 $

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Journal’s subject area:
Statistics and Probability;
Economics and Econometrics;
Computational Mathematics
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Abstract:
Mass imputation has been used in practice for combining non-probability and probability survey samples and making inferences on the parameters of interest using the information collected only in the non-probability sample. Under the assumption that the conditional mean function from the non-probability sample can be transported to the probability sample, we establish the consistency of the mass imputation estimator and derive its asymptotic variance formula. We also address important practical issues of the method through the analysis of a real-world non-probability survey sample collected by the Pew Research Centre.
Keywords:
auxiliary variables; bootstrap variance estimator; data integration; model transportability; selection bias

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