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http://dx.doi.org/10.5351/KJAS.2019.32.1.029

Sensitivity analysis of missing mechanisms for the 19th Korean presidential election poll survey  

Kim, Seongyong (Division of Big Data and Management Engineering, Hoseo University)
Kwak, Dongho (Division of Big Data and Management Engineering, Hoseo University)
Publication Information
The Korean Journal of Applied Statistics / v.32, no.1, 2019 , pp. 29-40 More about this Journal
Abstract
Categorical data with non-responses are frequently observed in election poll surveys, and can be represented by incomplete contingency tables. To estimate supporting rates of candidates, the identification of the missing mechanism should be pre-determined because the estimates of non-responses can be changed depending on the assumed missing mechanism. However, it has been shown that it is not possible to identify the missing mechanism when using observed data. To overcome this problem, sensitivity analysis has been suggested. The previously proposed sensitivity analysis can be applicable only to two-way incomplete contingency tables with binary variables. The previous sensitivity analysis is inappropriate to use since more than two of the factors such as region, gender, and age are usually considered in election poll surveys. In this paper, sensitivity analysis suitable to an multi-dimensional incomplete contingency table is devised, and also applied to the 19th Korean presidential election poll survey data. As a result, the intervals of estimates from the sensitivity analysis include actual results as well as estimates from various missing mechanisms. In addition, the properties of the missing mechanism that produce estimates nearest to actual election results are investigated.
Keywords
imputation; sensitivity analysis; incomplete contingency table; missing mechanism;
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