Determining the confidence interval for non-probabilistic surveys: Method proposal and validation
Jeanfrank Teodoro Dantas Sartori
Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 14, 4517-4525
Abstract:
This paper proposes a novel method for determining confidence intervals in non-probabilistic survey samples, addressing the challenge of statistically quantifying uncertainty in such samples. The method utilizes combinatorial calculations to assess the myriad combinations possible in the unsampled population, applying the symmetric property of binomial coefficients to optimize computational efficiency. The proposed approach offers a practical solution, making it feasible to calculate confidence intervals even with large sample sizes. This methodology represents a significant advancement in survey research, providing a tool to evaluate and generalize non-probabilistic data, particularly in contexts where probabilistic sampling is not viable. The paper also validates the method using extensive testing, demonstrating its applicability and effectiveness in real-world scenarios.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2024.2423815 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:54:y:2025:i:14:p:4517-4525
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2024.2423815
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().