• 제목/요약/키워드: survey data

검색결과 23,619건 처리시간 0.042초

국민건강영양조사 구강검사 개요 (Data resource profile: oral examination of the Korea National Health and Nutrition Examination Survey)

  • 우경지;이혜린;김윤정;김혜진;박덕영;김진범;오경원;최연희
    • Journal of Korean Academy of Oral Health
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    • 제42권4호
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    • pp.101-108
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    • 2018
  • Objectives: The Korea National Health and Nutrition Examination Survey (KNHANES) is a national surveillance system that has been assessing the health and nutritional status of Koreans since 1998. Based on the National Health Promotion Act, the surveys have been conducted by the Korea Centers for Disease Control and Prevention (KCDC). Methods: An oral examination as part of The National Health and Nutrition Examination was proposed to calculate the sample design and survey participation. The surveying system was presented by classifying the measurement environment, screening, and survey items by year, and the merits and limitations of using the data were suggested by examining the status of survey quality management and the process of disclosing raw data. Results: This nationally representative cross-sectional survey samples approximately 10,000 individuals each year and collects information on oral examinations and oral health interviews. Data for the oral health component of KNHANES was obtained to assess the oral health status of Koreans and determine the prevalence of dental caries and periodontitis. The oral health data quality control of KNHANES was composed of three parts: "Education Program" and "Field Training Program" for quality control of oral health examiners (dentists) by the professional academy, and "Data management" by the KCDC. After completion of the three-step data check, the indicators of dental caries, periodontal disease, and oral health behavior were published in the National Health Statistics. Conclusions: To achieve the goals of oral health indicators, we will continue to monitor so that we can use it as basic data for oral policies and carry out various linkage analyses related to oral diseases.

A Study on Nonresponse Errors in the Internet Survey

  • Namkung, Pyong;Kim, Min Jung
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.665-674
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    • 2002
  • The advantage of internet survey compared to the traditional survey methods are speedy in data collection, cost-effective, high performed design and able to data process and analysis at the same time. The other side are difficult to select sample, come from serious nonresponse errors. We suggest the new internet survey method to the questionnaire design that have the high response rate, enough to advanced preparations and system stability.

A FAST REDUCTION METHOD OF SURVEY DATA IN RADIO ASTRONOMY

  • LEE YOUNGUNG
    • 천문학회지
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    • 제34권1호
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    • pp.1-8
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    • 2001
  • We present a fast reduction method of survey data obtained using a single-dish radio telescope. Along with a brief review of classical method, a new method of identification and elimination of negative and positive bad channels are introduced using cloud identification code and several IRAF (Image Reduction and Analysis Facility) tasks relating statistics. Removing of several ripple patterns using Fourier Transform is also discussed. It is found that BACKGROUND task within IRAF is very efficient for fitting and subtraction of base-line with varying functions. Cloud identification method along with the possibility of its application for analysis of cloud structure is described, and future data reduction method is discussed.

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Analysis of Simultaneous Activities on the Time Use Survey Using Data Mining

  • 남기성;김희재
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2003년도 춘계학술대회
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    • pp.159-170
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    • 2003
  • This Paper analyzed simultaneous activities of the time use survey by Korea National Statistical Office to use data mining‘s association rule. The survey of National Statistical Office in 1999 considered general analysis for simultaneous activities. But if we use the association rule, we can found the ratio of particular activities at the same time. And we found the probability that another activities practise if we act one particular activity. Using this association rule of data mining we can do more developed and analytical sociological study.

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설문조사법을 통한 보존료의 일일 추정섭취량 평가 (Assessment of Estimated Daily Intakes for Preservatives from Survey Data)

  • 이창희;박성관;권우정;윤혜정;장영미;이종옥;이철원
    • 한국식품위생안전성학회지
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    • 제17권3호
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    • pp.166-172
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    • 2002
  • 보존료인 소르빈산 및 소르빈산칼륨, 안식향산 및 그 염류, 파라옥시안식향산에스테르류를 중심으로 식품첨가물의 일일추정섭취량을 평가하는 새로운 방법으로서 설문조사법을 제시하여 일일추정섭취량을 구하였을 때 조사한 보존료 모두 일일섭취허용량(ADI)의 1%미만으로 매우 안전한 수준이였다. 기존에 수행된 최대허용량을 이용한 단순추정방법 및 실제 분석치를 이용한 정밀추정방법과 비교ㆍ평가하였을 때, 설문조사법에 의한 총 일일추정섭취량은 소르빈산염류의 경우 0.39 mg/kg bw/day로 실제 분석치를 이용한 정밀조사방법에 의한 값인 0.22 mg/kg bw/day보다 높았으나 최대허용량을 이용한 방법에 의한 값인 1.39mg/kg bw/day보다는 훨씬 낮았다. 또한 안식향산염류와 파라옥시안식향산에스테르의 경우도 설문조사가 0.29 mg/kg bw/day, 0.03 mg/kg bw/day으로 정밀추정방법보다는 높게 나타났으나 단순추정방법인 최대허용량을 이용한 방법보다는 훨씬 낮은 값으로 정밀추정방법에 의한 값에 가까운 결과를 보였다. 따라서 설문조사법을 간편하고 경제적이면서 섭취량을 정밀하게 추정할 수 있는 식품첨가물 섭취량 평가의 방법으로 활용할 수 있을 것으로 사료된다.

PC를 이용한 천해저 탄성파탐사 자료 취득 및 처리에 관한 연구 (Data Acquisition and Processing for Shallow Marine Seismic Survey by Using a PC)

  • 김진후;김현도
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2001년도 춘계학술대회 논문집
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    • pp.166-171
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    • 2001
  • A digital seismic data acquisition and processing system using a PC has been developed in order to replace the analog data acquisition system of shallow marine seismic survey. An A/D converter that has 12bits of resolution and 225KHz of conversion rate was ued to acquire data, and a data acquisition software was developed as a Windows program which provides convenience of use. Raw data acquired at field has been saved to the hard-disk simultaneously. The signal to noise ratio, vertical and horizontal resolution could be improved by a digital data processing of the raw data. The digital processing of the raw data includss gain recovery, filtering, deconvolution, and muting. With the prediction deconvolution algorithm multiple reflections appearing on the shallow marine seismic section could be removed successfully.

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Imputation Using Factor Score Regression

  • Lee, Sang-Eun;Hwang, Hee-Jin;Shin, Key-Il
    • Communications for Statistical Applications and Methods
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    • 제16권2호
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    • pp.317-323
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    • 2009
  • Recently not even government polices but small town decisions are based on the survey data/information, so the most of government agencies/organizations demand various sample surveys in each fields for more detail information. However in conducting the sample survey, nonresponse problem rises very often and it becomes a major issue on judging the accuracy of survey. For that matters, one solution ran be using the administration data. However unfortunately most of administration data are restricted to the common users. The other solution can be the imputation. Therefore several method, of imputation are studied in various fields. In this study, in stead of the simple regression imputation method which is commonly used, factor score regression method is applied specially to the incomplete data which have the unit and item misting values in survey data. Here for simulation study, Consumer Expenditure Surveys in Korea are used.

데이터베이스 정규화 이론을 이용한 국민건강영양조사 중 다년도 식이조사 자료 정제 및 통합 (Data Cleaning and Integration of Multi-year Dietary Survey in the Korea National Health and Nutrition Examination Survey (KNHANES) using Database Normalization Theory)

  • 권남지;서지혜;이헌주
    • 한국환경보건학회지
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    • 제43권4호
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    • pp.298-306
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    • 2017
  • Objectives: Since 1998, the Korea National Health and Nutrition Examination Survey (KNHANES) has been conducted in order to investigate the health and nutritional status of Koreans. The food intake data of individuals in the KNHANES has also been utilized as source dataset for risk assessment of chemicals via food. To improve the reliability of intake estimation and prevent missing data for less-responded foods, the structure of integrated long-standing datasets is significant. However, it is difficult to merge multi-year survey datasets due to ineffective cleaning processes for handling extensive numbers of codes for each food item along with changes in dietary habits over time. Therefore, this study aims at 1) cleaning the process of abnormal data 2) generation of integrated long-standing raw data, and 3) contributing to the production of consistent dietary exposure factors. Methods: Codebooks, the guideline book, and raw intake data from KNHANES V and VI were used for analysis. The violation of the primary key constraint and the $1^{st}-3rd$ normal form in relational database theory were tested for the codebook and the structure of the raw data, respectively. Afterwards, the cleaning process was executed for the raw data by using these integrated codes. Results: Duplication of key records and abnormality in table structures were observed. However, after adjusting according to the suggested method above, the codes were corrected and integrated codes were newly created. Finally, we were able to clean the raw data provided by respondents to the KNHANES survey. Conclusion: The results of this study will contribute to the integration of the multi-year datasets and help improve the data production system by clarifying, testing, and verifying the primary key, integrity of the code, and primitive data structure according to the database normalization theory in the national health data.

자동주차조사 시스템 개발 및 활용에 관한 연구 (A Study on Development and Utilization of Automatic Parking Survey System)

  • 이영우;권혁준
    • 대한교통학회지
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    • 제32권5호
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    • pp.452-461
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    • 2014
  • 기존 주차조사는 광범위한 조사지역을 대상으로 조사원이 직접 주차차량의 번호판을 확인하는 방식으로 기동성의 저하, 조사와 입력의 이원화로 인한 입력오류, 많은 조사시간과 비용이 소요되는 단점을 가지고 있었다. 따라서 본 연구에서는 기존 조사원에 의한 주차조사의 단점을 극복하기 위해 최근 상용화된 고성능 영상분석장비, 위성측량장비, 적외선 조명 등을 이용하여 자동주차조사를 위한 방법에 관한 연구를 수행하였으며 본 연구결과 개발된 자동주차조사 방법을 이용하여 조사된 데이터를 수정, 저장, 분석 및 출력이 가능한 주차분석 소프트웨어를 개발하였다. 장비를 이용한 자동주차조사 시 조사차량의 주행속도, 영상분석장비의 촬영각도, 주차차량 상호간 차간간격, 조사차량과 주차차량의 이격거리 등에 의해 조사의 정밀도가 영향을 받는 것으로 나타나 장비를 이용한 자동주차조사의 정확도를 향상시키기 위해 실험을 통해 각 요소별 최적조합을 도출하였다. 또한 기존 주차조사 데이터가 체계적으로 저장, 관리되지 못하고 있는 문제점을 극복하고 주자정책 수립을 지원하기 위한 주차분석을 지원하기 위한 주차분석 소프트웨어를 개발하였다.

Inappropriate Survey Design Analysis of the Korean National Health and Nutrition Examination Survey May Produce Biased Results

  • Kim, Yangho;Park, Sunmin;Kim, Nam-Soo;Lee, Byung-Kook
    • Journal of Preventive Medicine and Public Health
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    • 제46권2호
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    • pp.96-104
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    • 2013
  • Objectives: The inherent nature of the Korean National Health and Nutrition Examination Survey (KNHANES) design requires special analysis by incorporating sample weights, stratification, and clustering not used in ordinary statistical procedures. Methods: This study investigated the proportion of research papers that have used an appropriate statistical methodology out of the research papers analyzing the KNHANES cited in the PubMed online system from 2007 to 2012. We also compared differences in mean and regression estimates between the ordinary statistical data analyses without sampling weight and design-based data analyses using the KNHANES 2008 to 2010. Results: Of the 247 research articles cited in PubMed, only 19.8% of all articles used survey design analysis, compared with 80.2% of articles that used ordinary statistical analysis, treating KNHANES data as if it were collected using a simple random sampling method. Means and standard errors differed between the ordinary statistical data analyses and design-based analyses, and the standard errors in the design-based analyses tended to be larger than those in the ordinary statistical data analyses. Conclusions: Ignoring complex survey design can result in biased estimates and overstated significance levels. Sample weights, stratification, and clustering of the design must be incorporated into analyses to ensure the development of appropriate estimates and standard errors of these estimates.