An Efficient Poisson-Distributed Adaptive Cluster Sampling Model Using Randomized Response Strategy

The key innovation lies in the incorporation of an adaptive cluster sampling strategy and a randomized response model based on the Poisson distribution. This integration aims to overcome shortcomings inherent in conventional models, providing a more robust framework for research area. In this paper,...

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Bibliographic Details
Published in:Ingénierie des systèmes d'Information 2024-08, Vol.29 (4), p.1315
Main Authors: Khalid Ul Islam Rather, Tanveer Ahmad Tarray, Olumide Sunday Adesina, Adedayo Funmi Adedotun, Toluwalase Janet Akingbade, Odekina, Onuche G
Format: Article
Language:fre
Subjects:
Adaptive sampling
Clusters
Data collection
Efficiency
Poisson distribution
Sample size
Sampling techniques
Social sciences
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Summary:The key innovation lies in the incorporation of an adaptive cluster sampling strategy and a randomized response model based on the Poisson distribution. This integration aims to overcome shortcomings inherent in conventional models, providing a more robust framework for research area. In this paper, an adaptive cluster sampling randomized response model with Poisson distribution using a randomized response strategy was proposed. The proposed cluster randomized response model has improved efficiency and a large gain in precision. Conditions were obtained under which the proposed model is more efficient than the existing models. To validate the effectiveness of our approach, numerical computations were conducted, offering concrete illustrations of the model's performance. The results underscore the significant gains in efficiency and precision achieved by the proposed adaptive cluster sampling randomized response model.
ISSN:1633-1311
2116-7125
DOI:10.18280/isi.290407