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http://dx.doi.org/10.5351/KJAS.2020.33.1.011

A study on non-response bias adjusted estimation in business survey  

Chung, Hee Young (Department of Statistics, Hankuk University of Foreign Studies)
Shin, Key-Il (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
The Korean Journal of Applied Statistics / v.33, no.1, 2020 , pp. 11-23 More about this Journal
Abstract
Sampling design should provide statistics to meet a given accuracy while saving cost and time. However, a large number of non-responses are occurring due to the deterioration of survey circumstances, which significantly reduces the accuracy of the survey results. Non-responses occur for a variety of reasons. Chung and Shin (2017, 2019) and Min and Shin (2018) found that the accuracy of estimation is improved by removing the bias caused by non-response when the response rate is an exponential or linear function of variable of interests. For that case they assumed that the error of the super population model follows normal distribution. In this study, we proposed a non-response bias adjusted estimator in the case where the error of a super population model follows the gamma distribution or the log-normal distribution in a business survey. We confirmed the superiority of the proposed estimator through simulation studies.
Keywords
linear response rate model; power response rate model; gamma distribution; log-normal distribution; super population model;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
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