• Title/Summary/Keyword: rim 가중법

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Propensity Adjustment Weighting of the Internet Survey by Volunteer Panel (자원자 패널에 의한 인터넷 조사의 성향조정 가중화)

  • Huh, Myung-Hoe;Cho, Sung-Kyum
    • Survey Research
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    • v.11 no.2
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    • pp.1-28
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    • 2010
  • This paper reports the results of the 2009 Internet volunteer panel version of the social survey conducted by Statistics Korea (Korea National Statistical Office). Authors identify socio-psychological characteristics of Internet survey volunteers and present quantitative evaluation of the propensity adjustment weighting method intended to remove Internet sample bias. The nine criteria used for propensity adjustment were regions, urban/rural, gender, age, education, consumer satisfaction, views on income distribution, newspaper access and Internet news access. Propensity adjustment weighting based on the logit model and rim weights were applied to the online survey of 2,903 respondents using the face-to-face area sample data of 37,049 respondents as reference. A total of 106 items were used for evaluating the propensity adjustment weighting methods. The results showed that in 80% of survey items the propensity adjustment weighting yielded better estimates compared to simple demographic weighting. This suggests that Internet surveys by volunteer panels are useful for conducting the general social study in Korea. The reference survey data for this study contains several items on social-psychological behaviors and attitudes, is large in size and obtained by probability sampling. Thus it may be utilized in propensity adjustment of other Internet surveys.

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Systematic Bias of Telephone Surveys: Meta Analysis of 2007 Presidential Election Polls (전화조사의 체계적 편향 - 2007년 대통령선거 여론조사들에 대한 메타분석 -)

  • Kim, Se-Yong;Huh, Myung-Hoe
    • The Korean Journal of Applied Statistics
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    • v.22 no.2
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    • pp.375-385
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    • 2009
  • For 2007 Korea presidential election, most polls by telephone surveys indicated Lee Myung-Bak led the second runner-up Jung Dong-Young by certain margin. The margin between two candidates can be estimated accurately by averaging individual poll results, provided there exists no systematic bias in telephone surveys. Most Korean telephone surveys via telephone directory are based on quota samples, with the region, the gender and the age-band as quota variables. Thus the surveys may result in certain systematic bias due to unbalanced factors inherent in quota sampling. The aim of this study is to answer the following questions by the analytic methods adopted in Huh et al. (2004): Question 1. Wasn't there systematic bias in estimates of support rates. Question 2. If yes, what was the source of the bias? To answer the questions, we collected eighteen surveys administered during the election campaign period and applied the iterated proportional weighting (the rim weighting) to the last eleven surveys to obtain the balance in five factors - region, gender, age, occupation and education level. We found that the support rate of Lee Myung-Bak was over-estimated consistently by 1.4%P and that of Jung Dong-Young was underestimated by 0.6%P, resulting in the over-estimation of the margin by 2.0%P. By investigating the Lee Myung-Bak bias with logistic regression models, we conclude that it originated from the under-representation of less educated class and/or the over-representation of house wives in telephone samples.

Unusual data local access using inverse order tree (역순트리를 이용한 특이데이터 국소적 접근)

  • Rim, Kwang-Cheol;Seol, Jung-Ja
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.3
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    • pp.595-601
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    • 2014
  • With the advent of the Smart information-communication era, the number of data has increased exponentially. Accordingly, figuring out and analyzing in which area and circumstance the data has been created becomes one of the factors for prompt actions. In this paper identifies how to analyze the data by implementing a route from the lowest module to highest one in an inverse order for the part judgement for the particular data. The script first identifies cluster analisys, paralizes the analysis using the sum of each factors of the cluster with the tree structure, and finally transpose the answer into number. Also, it is designed to place priority on particular answer, thereafter, draws the wanted answer real-time.