• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.587-598
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• 2016

In predicting an outcome of election using a variety of methods ahead of the election, non-response is one of the major issues. Therefore, to address the non-response issue, a variety of methods of non-response imputation may be employed, but the result of forecasting tend to vary according to methods. In this study, in order to improve electoral forecasts, we studied a model based method of non-response imputation attempting to apply the Monte Carlo Expectation Maximization (MCEM) algorithm, introduced by Wei and Tanner (1990). The MCEM algorithm using maximum likelihood estimates (MLEs) is applied to solve the boundary solution problem under the non-ignorable non-response mechanism. We performed the simulation studies to compare estimation performance among MCEM, maximum likelihood estimation, and Bayesian estimation method. The results of simulation studies showed that MCEM method can be a reasonable candidate for non-response model estimation. We also applied MCEM method to the Korean presidential election exit poll data of 2012 and investigated prediction performance using modified within precinct error (MWPE) criterion (Bautista et al., 2007).

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.57-67
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• 2006

In sampling survey, nonresponse tend to occur inevitably. If we use information from respondents only, the estimates will be baised. To overcome this, various non-response imputation methods have been studied. If there are few auxiliary variables for replacing missing imputation or spatial autocorrelation exists between respondents and nonrespondents, spatial autocorrelation can be used for missing imputation. In this paper, we apply several nonresponse imputation methods including spatial imputation for the analysis of farm household economy data of the Gangwon-Do in 2002 as an example. We show that spatial imputation is more efficient than other methods through the numerical simulations.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.195-199
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• 2003

Hansen과 Hurwitz(1946)는 우편조사에서의 무응답 문제를 처리하는 방법으로 표본을 응답결과에 따라 응답층과 무응답층으로 나눈 다음, 무응답층의 일부를 랜덤 추출하여 면대면 직접조사에 의해 무응답층의 정보를 얻는 방법을 제안하였다. 본 연구에서는 민감한 모집단에 대한 자료수집 방법으로 직접질문 방법인 Black-Box 방법과 간접질문 방법인 확률화응답기법(RRT)의 결합적 방법을 제시하였고, 층화이중 추출방법을 이용하여 모수를 추정하였다.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.29-40
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• 2019

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.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.311-328
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• 2005

This paper deals with a treatment of nonresponse in farm and fishery household economy surveys in Korea. Since the samples in two surveys were selected by stratified multi-stage sampling and weighted sample means has been used to estimate the population means, we choose a weighted hot-deck imputation method as an appropriate method for two surveys. We investigate the procedure of the weighted hot-deck as well as an adjusted jackknife method for variance estimation. Through an empirical study we found that the method worked very well in both mean and variance estimation in two surveys. In addition, we presented a procedure of forming imputation class and formed four imputation classes for each survey and then compared them with analysis. As a result, we presented two most efficient imputation classes for two surveys.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.143-148
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• 2003

표본조사에서 발생되는 무응답에 대한 대체법은 매우 다양하게 연구 되고 있다. 특히 모형을 기반으로 하는 회귀 대체법은 매우 활용도가 높다. 이 때 일반적으로 종속변수가 결측값의 변수가 되며 독립변수는 주어지게 된다. 주어지 주어진 종속변수와 독립변수의 값을 이용하여 모델을 설정하고 그에 따라 결측값을 예측하여 대체하게 된다. 이 때 예측값 즉 결측값을 구하는 과정에서 독립변수 값 자체에도 결측값이 생기게 된다는 것이다. 이때 여러 가지 방법으로 독립변수의 결측값을 대체하고 모형을 활용할 수 있다. 그러나 이 연구에서는 독립변수들을 같은 특성끼리 그룹화 시키는 요인분석(factor analysis)을 이용하여 독립변수의 결측값에따른 예측된 결측값의 변동을 최소화 하고자했다.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.409-420
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• 2020

In business survey, modified cut-off sampling is commonly used to greatly increase the accuracy of the estimation while reducing the number of samples. However, non-response rate of take-all stratum has increased significantly and the sample substitution is not possible because the non-response in the take-all stratum affects the accuracy of the estimation. It is important to adjust the bias appropriately if non-response is affected by the variable of interest. In this study, a bias adjusted estimation is proposed as an appropriate method to deal with a non-response in the take-all stratum. In particular, the estimator proposed by Chung and Shin (2020) was applied to the bias adjustment for the take-all stratum; therefore, we suggest a new method to adjust properly for the take-all stratum. The superiority of the proposed estimator was examined through simulation studies and confirmed through actual data analysis.

• Proceedings of the KAIS Fall Conference
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• 2007.11a
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• pp.57-59
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• 2007

정보보호시스템 평가수요의 예측은 예측된 평가수요를 근거로 적극적인 평가서비스를 제공하기 위하여 필요하다. 평가수요예측을 하기위하여 일반적으로 설문조사를 이용하지만 무응답 및 불성실한 응답으로 인하여 설문응답 자료만으로 평가수요를 예측하기에는 부족하다. 따라서 설문조사의 평가수요를 보정할 수 있는 모형이 필요하다. 본 논문에서는 설문조사를 통하여 예측 할 수 있는 직접적인 평가수요와 통계적 모형을 이용한 간접적 평가수요를 비교하고 설문조사의 대체 방법을 제시하였다.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.603-608
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• 2024

Nonresponse and missing values are caused by sample dropouts and avoidance of answers to surveys. In this case, problems with the possibility of information loss and biased reasoning arise, and a replacement of missing values with appropriate values is required. In this paper, as an alternative to missing values imputation, we compare several replacement methods, which use mean, linear regression, random forest, K-nearest neighbor, autoencoder and denoising autoencoder based on deep learning. These methods of imputing missing values are explained, and each method is compared by using continuous simulation data and real data. The comparison results confirm that in most cases, the performance of the random forest imputation method and the denoising autoencoder imputation method are better than the others.

• Survey Research
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• v.9 no.3
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• pp.71-91
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• 2008

Workplace Panel Survey(WPS) is the representative panel survey of workplace in Korea. WPS was newly sampled in 2005 and is to be used for the subsequent biennial survey. The main survey is divided into a questionnaire for human resources(HR) manager, a questionnaire for labor relations manager and a questionnaire for representatives of unions. The population of WPS 2005 included workplaces across the country with 30 or more employees. The WPS 2005 was composed of 1,905 workplaces including 290 workplaces in the public sector. The sample was selected by the stratified random sampling. Weighting process for the survey data was introduced to compensate for differential sampling and non-response rates. Personal interviews were conducted using the Computer Assisted Personal Interviewing(CAPI) system during visits by interviewers, along with survey via mail and e-mail concerning employment and financial issues. The CPAI system introduced for the WPS 2005 can by used for automatical detection for errors and inconsistencies which may occur during the survey process. The CAPI system played an important part in enhancing the reliability of the survey data.