• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.83-95
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• 1998

Statistical models are proposed for analyzing categorical data in the presence of missing observations or nonresponses which might occur in the sampling surveys and polls. As an illustration, we analyzed real polling data of the pre-presidential election in the USA, 1948, It had been predicted that Dewey would win the election. However, Truman won in the actual election.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.417-427
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• 2015

Measures in response rate used to measure the representativeness of the sample (the more high response rate) better explain the representativeness of the sample. However, we cannot often explain the representativeness of the sample because there is nonresponse even in the high response rate. Therefore, Schouten et al. (2009) presented a new R-indicator measure that can be described as a representative of the sample. We research the new estimator of the R-indicator in this paper because there are parameters that require estimations. We describe the meanings as representative of the R-indicator; consequently, the bias and efficiency of the proposed estimator for R-indicator are compared to the existing estimator under various simulations. The representativeness of the sample is also explained by applying the proposed estimators in the actual data.

• Survey Research
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• v.11 no.3
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• pp.33-55
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• 2010

In this study, we newly define the Total Survey Error(TSE) in exit poll and investigate the TSEs of the exit poll survey for the 18th general election of 2008 to analyse the cause of the exit poll prediction error. To explore the main cause and effect of the total survey error, the total survey error was divided by the sampling error which comes from sampling process of poll stations and the non-sampling error which comes from selecting voter and collecting responses from sampled voters in each electoral district. We consider the relationship between non-response rates and total survey error as well as non-sampling error. Also, we study the representativeness of the exit poll sample by comparing the sex/age distribution of the exit poll data and the National Election Commission poll data.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.149-151
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• 2002

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1315-1329
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• 2009

The panel survey is need to have a more concern about a response due to a secession and non-response of a sample. And generally a population is not fixed and continuously changed. Thus, the rotation sample design can be used by the method replacing the panel research. This paper is the study of comparison to equal weight method, Duncan weight, Design weight method, weight share method in rotation sample design. More specifically, this paper compared variance estimators about the existing each method for the efficiency comparison, and to compare the precision using the relative efficiency gain by the Coefficient Variance(CV) after getting the design weight from the actual data.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.533-543
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• 2010

Asking sensitive questions by a direct survey method causes non-response bias and response bias. Non-response bias arises from interviewees refusal to respond and response bias arises from giving incorrect responses. To rectify these biases, Warner (1965) introduced a randomized response model which is an alternative survey method for socially undesirable or incriminating behavior questions. The randomized response model is a procedure for collecting the information on sensitive characteristics without exposing the identity of the respondent. Many survey researchers have proposed diverse variants of the Warner randomized response model and applied their model to collect the information of sensitive questions. Using an optimal allocation, we proposed three-stage stratified randomized response technique which is an extension of the Kim and Elam (2005) two-stage stratified randomized response technique. In this study, we showed that the estimator based on the proposed response model is more efficient than Kim and Elam (2005). But by adding one more survey step to the Kim and Elam (2005), our proposed model may have relatively less privacy protection compared to the Kim and Elam (2005) model.

• Journal of Korea Fishing Vessel Association
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• v.11
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• pp.48-51
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• 1982

• Proceedings of the Korean Nuclear Society Conference
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• 1995.05b
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• pp.999-1004
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• 1995

본 논문에서는 현재 수행 중인 Hualien 대형내진모델시험 프로젝트의 연구 과제 중의 강제 진동 해석 및 지진 응답 해석을 수행하기 위계서 Hyperelement를 사용한 지반-구조물 상호작용 해석에 대한 절차 및 방법을 연구하였다. Hualien 대형내진모델시험에서 이미 수행된 뒷채움 후 강제 진동 시험의 예 측 및 예측후 해석을 수행하였고, 지진 응답 해석을 위해서는 Hualien부지에서의 자유장해석을 통하여 입력 지반 운동을 결정하여 구조물에서의 지진 응답을 구하였다.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.671-683
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• 2021

Power allocation is a technique that evenly allocates samples for each stratum, although the overall efficiency of the allocation is less than that of optimal allocation, and it is often used as a square root proportional allocation in real survey. Also, considering the non-response that occurs in real survey, a larger sample size is used than that in the theoretical formula. In this study, in determining the sample size for each stratum, we study the new methods of allocating by adding information on the response rate per each stratum to power allocation method. The proposed allocation methods are compare with proportional, optimal, and square root proportional allocation in simulation. In addition, the comparison with the proportional and optimal allocation to which the response rate was added is examined through simulation. As a result, we examine the advantages and disadvantages of the allocation methods.

• Survey Research
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• v.7 no.2
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• pp.71-95
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• 2006

This article presents strengths of Computer-Assisted Personal Interviewing(CAPI) in social surveys with complicated questionnaires, from examples of a pilot and the first year surveys of the Korean Longitudinal Study of Ageing(KLoSA). This study focuses on how to improve the quality of data by using CAPI and finds five strengths among others. First of all, CAPI can contribute to reducing response errors by structuring the logic and path of questionnaires, setting a response range, and maintaining response consistency. Second, CAPI enhances convenience of interviewing by allowing customized questions and automatic calculation and scoring. It also allows the 'help' function. Third, its random arrangement of questions prevents response order effect and/or questions order effect. Fourth, CAPI can raise the response rate by reducing item non-responses. Fifth, it makes it easy monitoring interviewing, thus helps supervising interviewers and modifying questionnaires when necessary. These merits of CAPI contribute to reducing possible errors in the process of interviewing, therefore improve the data quality.