• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1397-1405
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• 2014

설문조사에서는 대부분 단위무응답 또는 항목무응답이 발생한다. 무응답 발생비율이 높은 경우 무응답을 무시한 분석은 잘못된 결과를 초래할 수도 있으므로 무응답에 대한 특성 파악도 필요하다. 횡단자료에서는 항목무응답 특성에 대한 연구는 가능하나 단위무응답의 특성을 파악하기가 어렵다. 단위무응답의 특성을 파악하기 위하여 본 논문에서는 종단자료인 한국아동 청소년패널조사 중 중1패널자료를 이용하였다. 최근까지 공개된 한국아동 청소년패널조사자료를 이용한 논문들의 무응답 처리 실태를 파악하고, 그 중 단위무응답의 특성에 대하여 분석하였다. 이 자료를 이용한 논문에서는 대부분 단위무응답의 처리를 제거하는 방식을 취하고 있으며, 이 자료에서 제공하고 있는 가중치를 이용한 논문은 거의 없었다. 이에 단위무응답의 처리방법 중 가중치를 이용한 방법과 그 대상을 제외하는 두 가지 방법에 대해 여러 가지 특성들의 분석을 비교하였다. 많은 항목에서 두 가지 방법의 결과가 상이하게 나타났으며, 가중치를 이용한 경우가 제거법에 의한 결과에 비해 통계적으로 유의한 결과가 더 많이 나타나 무응답에 대해 많은 논의가 필요할 것으로 생각된다.

• Asian Journal for Public Opinion Research
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• 제3권3호
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• pp.111-130
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• 2016

Researchers have been perplexed by the issue of unit nonresponse since the beginning of practicing survey research and have been attentive to the causes that lead to the occurrence of unit nonresponse as well as the impact of unit nonresponse. However, because researchers have little to no information regarding unit nonrespondents, it is unlikely that they are able to examine the differences between participants and nonrespondents to estimate the loss of representativeness in the final sample compared with the target population. Therefore, the lack of information regarding the absentees complicates addressing the unit nonresponse bias in a satisfactory manner. Therefore, the purpose of this study was to determine the demographic characteristics and political attitudes of nonrespondents by relying on information provided by their spouses, which was obtained through a telephone survey conducted in Taiwan. It is found that demographic variables as well as political attitudes are related to the likelihood of an individual becoming a unit nonrespondent in telephone surveys.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.665-678
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• 2003

In this paper we suggest the new calibration estimator, which is called to the recalibration estimator, and its variance estimator using two-phase sampling technique according to the auxiliary information having strong correlation with the variable of interest under the unit nonresponse. In this unit nonresponse situation, an available information may exists at the level of whole population or the first-phase sample. The proposed recalibration estimator derives from the first and second phase weights respectively.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1183-1194
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• 2012

설문조사를 실시할 경우 무응답이 발생하지 않는 경우는 매우 드문일이며 무응답이 발생할 경우 무응답처리에 대해서는 다양한 방법이 적용되고 있다. 본 논문에서는 무응답의 두 가지 유형인 단위무응답과 항목무응답의 발생비율을 기존에 조사된 실제 사례를 이용하여 파악하였으며, 무응답률에 따른 분석결과의 차이를 비교하였다. 또한, 대학생들을 대상으로 집단면접조사를 통해 직접 자료를 수집하였고 이 자료를 바탕으로 무응답률과 무응답이 발생하는 이유를 제시하였다.

• 품질경영학회지
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• 제28권2호
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• pp.123-134
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• 2000

In the survey, it is very hard to get the complete response. Because the respondents tend to refuse to the questionnaire with something like incomes of the individual or may not be at home in the survey time. These nonresponses are classified into two groups as the item nonresponse and the unit nonresponse. When the nonresponse happen to the special item of the questionnaire, it is caned item nonresponse. On the other hand the unit nonresponse occurs to the totally missing in questionnaire. In this paper, we only consider to the unit nonresponse situation. We propose that the optimal estimator which is minimized the variance of the estimator under a fixed cost function for the survey and response.

• Journal of applied mathematics & informatics
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• 제9권2호
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• pp.869-877
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• 2002

In the presence of unit nonresponse we perform the calibration estimation procedure for the population total corresponding to the levels of auxiliary information and derive the Taylor and the Jackknife variance estimators of it. We study the nonresponse bias reduction and the variance stabilization, and then show the efficiency of the Taylor and the Jackknife variance estimators by simulation study.

• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2005년도 추계학술대회 발표논문집
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• pp.169-183
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• 2005

가중치 조정(weighting adjustment)으로 단위 무응답(unit nonresponse)을 처리하는 문제에서 성향점수를 추정하는 모형을 만들기 위해 응답변수와 관심변수를 동시에 고려하는 다변량 회귀나무(multivariate regression tree)기법을 제안하였다. 효과적인 무응답 조정층 구축을 위해 응답한 개체들만 사용하는 경우와 모든 개체들을 사용하는 경우를 제시하고 이 두방법을 편향의 관점으로 비교한다.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.479-489
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• 2002

The case which applies two-phase sampling to stratification and nonresponse problem, it is a poweful and effective technique. In this paper we study the calibration estimator and its variance estimator for the population total using two-phase sampling method according to the of auxiliary information for population and sample having strong correlation with an interested variable in unit nonresponse situation. The auxiliary information that available both at first-phase and second-phase sampling can be used to improve weights by the calibration procedure. A weight which corresponds to the product of sampling weights and response probability is calculated at each phase of sampling.

• 품질경영학회지
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• 제26권3호
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• pp.82-99
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• 1998

In sampling survey the nonresponse reduces the precision of the estimator becuase of the nonresponse bias of the estimator. Deville, et al.(1993) considered the generalized raking procedure with the auxiliary information under five distance measures for reducing the nonresponse bias of the estimator. This paper extends the classical weighting adjustment of Deville, et al.(1993) to the stratified sampling case with three among five measures.

• Journal of the Korean Data and Information Science Society
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• 제27권1호
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• pp.245-254
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• 2016

Many surveys provide categorical data and there may be one or more missing categories. We describe a nonignorable nonresponse model for the analysis of two-way contingency tables from small areas. There are both item and unit nonresponse. One approach to analyze these data is to construct several tables corresponding to missing categories. We describe a hierarchical Bayesian model to analyze two-way categorical data from different areas. This allows a "borrowing of strength" of the data from larger areas to improve the reliability in the estimates of the model parameters corresponding to the small areas. Also we use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data on thirteen states to obtain the finite population proportions.