• Survey Research
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• v.11 no.3
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• pp.1-18
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• 2010

How much do people living in different communities vary in their survey responses? A few studies have examined the effect of the social environment on survey response. Making generalizations from these studies by looking at the effect of social environment on survey response is complicated due to differences in survey dimensions, including incentives, survey mode, types of response rates, and geographic levels. Using the 2000 Census Final Response Rates(CFRR) and the 2002 General Social Survey Response Rates(GSSRR) linked with the 2000 Census in the United States, we attempt to understand how community characteristics associated with survey cooperation vary between data sets. We found that people living in poor area are less likely to cooperate with the Census but more likely to cooperate with GSS, while people living in an area with more minors under 18 is more likely to cooperate with both Census and the GSS. By using two data sources with contrasting survey dimensions within the United States, our findings have implications for survey field operations and hopefully will invigorate studies about response rates in a Korean context.

• Asian Journal for Public Opinion Research
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• v.1 no.2
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• pp.128-146
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• 2014

Incentives are often included in survey design because they are known to improve response rates, at least moderately. This paper describes the changes in the response rates when incentives were introduced into a longitudinal survey. The National Survey of Student Engagement was conducted annually at Indiana University Bloomington from 2000 through 2012. In 2010, incentives were introduced in an attempt to reverse the declining response rates. The incentives performed as expected, raising the AAPOR Response Rate 3 from 24% in 2009 to 36% in 2010. From 2010 through 2012, different types of incentives were tried but the response rates did not change substantially. The results from the changes in incentives can help survey practitioners decide the number and types of incentives that might be used effectively to increase response rates.

• Journal of Korea Technology Innovation Society
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• v.5 no.2
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• pp.228-244
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• 2002

The survey of research and development (R&D) in science and technology (S&T) covers the current status of R&D activities in S&T in Korea, and provides a basis for decision making regarding S&T policy. Continuous improvement of the survey is widely needed to present reliable national basic statistics. Therefore, the purpose of the study is two-fold: to introduce sampling survey method in industrial sector and to make statistical technique to deal with non-response data from industrial sector. To these ends, first, case studies of the United States and Japan are illustrated. A new sampling design for the R&D survey is proposed and implementing stratified random sampling scheme is suggested. Moreover, statistical analysis of the non-response data is dealt with. Based on several screening criteria, we develop a new imputation method suitable for the R&D survey and also provide more detailed implementation plan. Various solutions to a problem arising from non-response item are also presented. Finally, some implications of the results are discussed.

• Proceedings of the Korean Association for Survey Research Conference
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• 2007.11a
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• pp.213-230
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• 2007

Although the response model has been frequently applied to nonresponse weighting adjustment or imputation, the estimation under callbacks has been relatively underdeveloped in the response model. The estimation method using the response probability is developed under callbacks. A replication method for the estimation of the variance of the proposed estimation is also developed. Since the true response probability is usually unknown, we study the estimation of the response probability. Finally, we propose an estimator under callbacks using the ratio imputation as well as the response probability. The simulation study illustrates our techniques.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1237-1250
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• 2006

In this paper we develop the web-based unified randomized response system for obtaining more reliable response to the sensitive characteristic such as a crime of violence at home, and a bribing and so on. This survey system embody to apply with from the classical to recently research, for example from the Warner's model to the 2-stage model. In addition, our survey system is able to link between the typical and the randomized response system. Finally, our survey system looks into a variation according to various sensitive questions as well as it can be used for a single question.

• Survey Research
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• v.12 no.2
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• pp.51-76
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• 2011

Analyzing the 2009 Korean General Social Survey(KGSS), this study attempts to elucidate the mechanism how content-irrelevant response patterns are formed in the social survey. This study investigates the relationship between personality traits and response styles. Specifically, the effects of Big Five factors(extraversion, agreeableness, conscientiousness, emotional stability, openness to experience) of personality on the acquiescent response styles(ARS) and extreme response styles(ERS) are examined, controlling for individual characteristics and interview contexts. The results show that ERS is positively affected by extraversion, openness to experience, agreeableness, and conscientiousness, whereas ARS is not significantly associated with any dimension of personality traits. The implications of findings and the methods to reduce response bias are discussed.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.731-737
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• 2001

In this paper, we suggest and implement an internet survey system cooperating the randomized response technique(RRT). We compare it with the direct survey. RRT is an indirect survey method to get true information from the respondent who is conceived to have sensitive character without revealing his/her status. We implement our system(method) based a data-base system, so it common all kind of data obtained through internet surveys. This system also can be used in spot survey independently.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.375-387
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• 2013

Unit non-response of surveys reduces the efficiency of the estimates and also causes non-response bias especially when there is large difference between respondents and non-respondents. Non-response weighting adjustments have usually been used to compensate for non-response. It is not easy to examine the non-response bias as well as to obtain information on the non-respondents in sample surveys. A household panel survey, called The Survey of Household Finances, was conducted in both 2010 and 2011. In this paper, we assume that non-response households in Wave 2 have strong non-response (non-cooperative) tendency. We classify those households into non-response households in Wave 1. Under this assumption, the characteristics of non-response households, the non-response bias and the effect of non-response adjustments are investigated.

• 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 the Korean Data and Information Science Society
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• v.15 no.4
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• pp.731-741
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• 2004

This paper is planned to use multi-proportions randomized response model for sensitive information on internet survey. This is an indirect response technique as a way of obtaining much more precise information. In this system we consider that respondents are generally reluctant to answer in a survey to get sensitive information targeting employees, customers, etc.