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      KCI등재후보

      Linear Measurement Error Variance Estimation based on the Complex Sample Survey Data

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      https://www.riss.kr/link?id=A104955530

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      다국어 초록 (Multilingual Abstract)

      Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES Ⅲ) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.
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      Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term...

      Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES Ⅲ) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.

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      참고문헌 (Reference)

      1 M. P. Cooper, "Web Surveys: a Review of Issues and Approaches" 64 : 464-494, 2000

      2 M. Davidian, "Variance function estimation" 82 : 1097-1091, 1987

      3 J. L. Eltinge, "Use of propensity models in the analysis of subsample re-measurements for NHANES III" Statistical Society of Canada 27-36, 1997

      4 T. E. Dalenius, "The survey statistician's reponsibility for both sampling and measurement errors, In Current Topics in Survey Sampling" Academic Press 17-29, 1981

      5 J. Shao, "Resampling methods in sample surveys (with discussion)" 27 : 203-254, 1996

      6 W. A. Fuller, "Regression estimation in the presence of measurement error, In Measurement Errors in Surveys" John Wiley & Sons 616-635, 1991

      7 P. P. Biemer, "Measurement Errors in Surveys" John Wiley & Sons 1991

      8 M. Davidian, "Estimation of variance functions in assays with possibly unequal replication and nonnormal data" 77 : 43-54, 1990

      9 R. J. Carroll, "Approximate quasi-likelihood estimation in models with surrogate predictors" 85 : 652-663, 1990

      10 R. J. Carroll, "An asymptotic theory for weighted least -squares with weighted by replication" 10 : 478-486, 1988

      1 M. P. Cooper, "Web Surveys: a Review of Issues and Approaches" 64 : 464-494, 2000

      2 M. Davidian, "Variance function estimation" 82 : 1097-1091, 1987

      3 J. L. Eltinge, "Use of propensity models in the analysis of subsample re-measurements for NHANES III" Statistical Society of Canada 27-36, 1997

      4 T. E. Dalenius, "The survey statistician's reponsibility for both sampling and measurement errors, In Current Topics in Survey Sampling" Academic Press 17-29, 1981

      5 J. Shao, "Resampling methods in sample surveys (with discussion)" 27 : 203-254, 1996

      6 W. A. Fuller, "Regression estimation in the presence of measurement error, In Measurement Errors in Surveys" John Wiley & Sons 616-635, 1991

      7 P. P. Biemer, "Measurement Errors in Surveys" John Wiley & Sons 1991

      8 M. Davidian, "Estimation of variance functions in assays with possibly unequal replication and nonnormal data" 77 : 43-54, 1990

      9 R. J. Carroll, "Approximate quasi-likelihood estimation in models with surrogate predictors" 85 : 652-663, 1990

      10 R. J. Carroll, "An asymptotic theory for weighted least -squares with weighted by replication" 10 : 478-486, 1988

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2022 평가예정 신규평가 신청대상 (신규평가)
      2021-12-01 평가 등재후보 탈락 (계속평가)
      2020-12-01 평가 등재후보로 하락 (재인증) KCI등재후보
      2017-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2013-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2012-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2010-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.45 0.45 0.35
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.28 0.25 0.24 0.05
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