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An Estimation of Sensitive Attribute Applying Geometric Distribution under Probability Proportional to Size Sampling

Gi-Sung Lee (), Ki-Hak Hong () and Chang-Kyoon Son ()
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Gi-Sung Lee: Department of Children Welfare, Woosuk University, Wanju Jeonbuk 55338, Korea
Ki-Hak Hong: Department of Computer Science, Dongshin University, Naju Jeonnam 58245, Korea
Chang-Kyoon Son: Department of Applied Statistics, Dongguk University, Gyeongju Gyeongbuk 38066, Korea

Mathematics, 2019, vol. 7, issue 11, 1-16

Abstract: In this paper, we extended Yennum et al.’s model, in which geometric distribution is used as a randomization device for a population that consists of different-sized clusters, and clusters are obtained by probability proportional to size (PPS) sampling. Estimators of a sensitive parameter, their variances, and their variance estimators are derived under PPS sampling and equal probability two-stage sampling, respectively. We also applied these sampling schemes to Yennum et al.’s generalized model. Numerical studies were carried out to compare the efficiencies of the proposed sampling methods for each case of Yennum et al.’s model and Yennum et al.’s generalized model.

Keywords: probability proportional to size (PPS) sampling; geometric distribution; sensitive attribute; randomization device; Yennum et al.’s model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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