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1 "Hyemi Moon"
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Original Article
Item non-response imputation in the Korea National Health and Nutrition Examination Survey
Serhim Son, Hyemi Moon, Hyonggin An
Epidemiol Health. 2022;44:e2022096.   Published online October 28, 2022
DOI: https://doi.org/10.4178/epih.e2022096
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AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
The Korea National Health and Nutrition Examination Survey (KNHANES) is a public health survey that assesses individuals’ health and nutritional status and monitors the prevalence of major chronic diseases. In general, sampling weights are adjusted for unit non-responses and imputation is conducted for item non-responses. In this study, we proposed strategies for imputing item non-responses in the KNHANES in order to improve the usefulness of data, minimize bias, and increase statistical power.
METHODS
After applying logical imputation, we adopted 2 separate imputation methods for each variable type: unweighted sequential hot-deck imputation for categorical variables and sequential regression imputation for continuous variables. For variance estimation, multiple imputations were applied to the continuous variables. To evaluate the performance of the proposed strategies, we compared the marginal distributions of imputed variables and the results of multivariable regression analysis for the complete-case data and the expanded data with imputed values, respectively.
RESULTS
When comparing the marginal distributions, most non-responses were imputed. The multivariable regression coefficients presented similar estimates; however, the standard errors decreased, resulting in statistically significant p-values. The proposed imputation strategies may cope with the loss of precision due to missing data, thus enhancing statistical power in analyses of the KNHANES by providing expanded data with imputed values.
CONCLUSIONS
The proposed imputation strategy may enhance the utility of data by increasing the number of complete cases and reducing the bias in the analysis, thus laying a foundation to cope with the occurrence of item non-responses in further surveys.
Summary
Korean summary
본 연구는 국민건강영양조사에서 발생한 항목무응답의 대체방법에 대해 연구한다. 본 논문에서 제시된 논리적 대체와 무응답 대체법을 이용해 대체된 데이터를 제공함으로써 결과의 편향 감소와 통계적 검정력 향상을 기대할 수 있다. 또한, 본 연구의 결과는 추후 데이터 수집시 발생하는 무응답 발생의 최소화를 위한 대책마련에 사용될 수 있다.
Key Message
The proposed logical imputation and item non-response imputation strategy may enhance the utility of data by increasing the number of complete cases and reducing the bias in the analysis, thus laying a foundation to cope with the occurrence of item non-responses in further surveys.

Epidemiol Health : Epidemiology and Health