Campus Units

Statistics

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

1-1-2019

Journal or Book Title

arxiv

Abstract

This paper presents theoretical results on combining non-probability and probability survey samples through mass imputation, an approach originally proposed by Rivers (2007) as sample matching without rigorous theoretical justification. Under suitable regularity conditions, we establish the consistency of the mass imputation estimator and derive its asymptotic variance formula. Variance estimators are developed using either linearization or bootstrap. Finite sample performances of the mass imputation estimator are investigated through simulation studies and an application to analyzing a non-probability sample collected by the Pew Research Centre.

Comments

This pre-print is made available through arxiv: https://arxiv.org/abs/1812.10694v2.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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