We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Integrating probability and big non-probability samples data to produce Official Statistics.
- Authors
Golini, Natalia; Righi, Paolo
- Abstract
This paper introduces the pseudo-calibration estimators, a novel method that integrates a non-probability sample of big size with a probability sample, assuming both samples contain relevant information for estimating the population parameter. The proposed estimators share a structural similarity with the adjusted projection estimators and the difference estimators but they adopt a different inferential approach and informative setup. The pseudo-calibration estimators can be employed when the target variable is observed in the probability sample and, in the non-probability sample, it is observed correctly, observed with error, or predicted. This paper also introduces an original application of the jackknife-type method for variance estimation. A simulation study shows that the proposed estimators are robust and efficient compared to the regression data integration estimators that use the same informative setup. Finally, a further evaluation using real data is carried out.
- Subjects
NONPROBABILITY sampling; PARAMETERS (Statistics); STATISTICS; SAMPLE size (Statistics); PROBABILITY theory; DATA integration
- Publication
Statistical Methods & Applications, 2024, Vol 33, Issue 2, p555
- ISSN
1618-2510
- Publication type
Article
- DOI
10.1007/s10260-023-00740-y