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1 "Ordinary statistical data analysis"
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Original Article
Inappropriate Survey Design Analysis of the Korean National Health and Nutrition Examination Survey May Produce Biased Results
Yangho Kim, Sunmin Park, Nam-Soo Kim, Byung-Kook Lee
J Prev Med Public Health. 2013;46(2):96-104.   Published online March 28, 2013
DOI: https://doi.org/10.3961/jpmph.2013.46.2.96
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AbstractAbstract PDF
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.

Summary

Citations

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JPMPH : Journal of Preventive Medicine and Public Health