Item non-response imputation in the Korea National Health and Nutrition Examination Survey

• 발행기관: 한국역학회
• 저자명: Serhim Son Hyemi Moon Hyonggin An
• 간행물 정보: 『Epidemiology and Health』44, 1~9쪽, 전체 9쪽
• 주제분류: 의약학 > 면역학
• 파일형태: PDF
• 발행일자: 2022.01.01

영문 초록

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.

키워드

Korea National Health and Nutrition Examination Survey Methods Sample size Database