Inappropriate survey design analysis of the Korean National Health and Nutrition Examination Survey may produce biased results.

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 res...

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Publicado en:Journal of Preventive Medicine & Public Health Vol. 46; no. 2; pp. 96 - 105
Autores principales: Kim, Yangho, Park, Sunmin, Kim, Nam-Soo, Lee, Byung-Kook
Formato: research Journal Article
Publicado: Korean Society for Preventive Medicine Mar2013
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2013
      vid: 46
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      pub: Korean Society for Preventive Medicine
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        10.3961/jpmph.2013.46.2.96
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        atl: Inappropriate survey design analysis of the Korean National Health and Nutrition Examination Survey may produce biased results.
      aug:
        au:
          Kim, Yangho
          Park, Sunmin
          Kim, Nam-Soo
          Lee, Byung-Kook
        affil: Department of Occupational and Environmental Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea.
      sug:
        subj:
          Study Design
          Surveys
          Adult
          Aged
          Blood Pressure
          Bone Density
          Cadmium Blood
          Creatinine Blood
          Female
          Hemoglobins Analysis
          Human
          Lead Blood
          Male
          Mercury Blood
          Middle Age
          PubMed
          South Korea
          Adult: 19-44 years
          Aged: 65+ years
          Middle Aged: 45-64 years
          Female
          Male
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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