[논문]불검출 자료를 포함한 작업환경측정 자료의 분석 방법 비교

박주현; 최상준; 고동희; 박동욱; 성예지

doi:10.15269/jksoeh.2022.32.1.21

불검출 자료를 포함한 작업환경측정 자료의 분석 방법 비교
A Comparison of Analysis Methods for Work Environment Measurement Databases Including Left-censored Data 원문보기

한국산업보건학회지 = Journal of Korean Society of Occupational and Environmental Hygiene, v.32 no.1, 2022년, pp.21 - 30

박주현 (동국대학교 통계학과) , 최상준 (가톨릭대학교 보건의료경영대학원) , 고동희 (가톨릭관동대학교) , 박동욱 (한국방송통신대학교) , 성예지 (가톨릭대학교 보건의료경영대학원)

Abstract ▼ AI-Helper

Objectives: The purpose of this study is to suggest an optimal method by comparing the analysis methods of work environment measurement datasets including left-censored data where one or more measurements are below the limit of detection (LOD). Methods: A computer program was used to generate left-censored datasets for various combinations of censoring rate (1% to 90%) and sample size (30 to 300). For the analysis of the censored data, the simple substitution method (LOD/2), β-substitution method, maximum likelihood estimation (MLE) method, Bayesian method, and regression on order statistics (ROS)were all compared. Each method was used to estimate four parameters of the log-normal distribution: (1) geometric mean (GM), (2) geometric standard deviation (GSD), (3) 95th percentile (X95), and (4) arithmetic mean (AM) for the censored dataset. The performance of each method was evaluated using relative bias and relative root mean squared error (rMSE). Results: In the case of the largest sample size (n=300), when the censoring rate was less than 40%, the relative bias and rMSE were small for all five methods. When the censoring rate was large (70%, 90%), the simple substitution method was inappropriate because the relative bias was the largest, regardless of the sample size. When the sample size was small and the censoring rate was large, the Bayesian method, the β-substitution method, and the MLE method showed the smallest relative bias. Conclusions: The accuracy and precision of all methods tended to increase as the sample size was larger and the censoring rate was smaller. The simple substitution method was inappropriate when the censoring rate was high, and the β-substitution method, MLE method, and Bayesian method can be widely applied.

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표/그림 (4)

그림 Fig. 1. A graphical diagram on the simulation study design. The dashed line means that the rest of the items proceed the same (AM: arithmetic mean, GM: geometric mean, GSD: geometric standard deviation, X95: 95^th percentile, LOD: limit of detection, MLE: maximum likelihood estimation, ROS: regression on order statistics).
그림 Fig. 2. Relative bias of AM (a), GM (b), GSD (c), and X95 (d) estimated by five censoring data analysis methods for datasets generated by a combination of censoring rate and sample size (AM: arithmetic mean, GM: geometric mean, GSD: geometric standard deviation, X95: 95^th percentile, LOD: limit of detection, MLE: maximum likelihood estimation, ROS: regression on order statistics).
그림 Fig. 3. Relative rMSE of AM (a), GM (b), GSD (c), and X95 (d) estimated by five censoring data analysis methods for datasets generated by a combination of censoring rate and sample size (AM: arithmetic mean, GM: geometric mean, GSD: geometric standard deviation, X95: 95^th percentile, LOD: limit of detection, MLE: maximum likelihood estimation, ROS: regression on order statistics, rMSE: root mean square error).
표 Table 1. Censoring data analysis methods with good performance by sample size and the degree of censoring

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불검출 자료를 포함한 작업환경측정 자료의 분석 방법 비교
A Comparison of Analysis Methods for Work Environment Measurement Databases Including Left-censored Data 원문보기

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불검출 자료를 포함한 작업환경측정 자료의 분석 방법 비교 A Comparison of Analysis Methods for Work Environment Measurement Databases Including Left-censored Data 원문보기

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불검출 자료를 포함한 작업환경측정 자료의 분석 방법 비교
A Comparison of Analysis Methods for Work Environment Measurement Databases Including Left-censored Data 원문보기

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