Estimating General Parameters from Non-Probability Surveys Using Propensity Score Adjustment

Luis Castro-Martín, María del Mar Rueda and Ramón Ferri-García
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Luis Castro-Martín: Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain
María del Mar Rueda: Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain
Ramón Ferri-García: Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain

Mathematics, 2020, vol. 8, issue 11, 1-14

Abstract: This study introduces a general framework on inference for a general parameter using nonprobability survey data when a probability sample with auxiliary variables, common to both samples, is available. The proposed framework covers parameters from inequality measures and distribution function estimates but the scope of the paper is broader. We develop a rigorous framework for general parameter estimation by solving survey weighted estimating equations which involve propensity score estimation for units in the non-probability sample. This development includes the expression of the variance estimator, as well as some alternatives which are discussed under the proposed framework. We carried a simulation study using data from a real-world survey, on which the application of the estimation methods showed the effectiveness of the proposed design-based inference on several general parameters.

Keywords: nonprobability surveys; propensity score adjustment; survey sampling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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