Statistical methods for handling nondetected results in food chemical monitoring data to improve food risk assessments
نویسندگان
چکیده
Chemical risk assessment is important for management, and estimates of chemical exposure must be as accurate possible. concentrations in food below the limit detection are known nondetects result left-censored data. During statistical analysis, method used handling values important. Many assessors employ widely substitution methods to treat data, recommended by international organizations. The National Institute Food Drug Safety Evaluation South Korea also recommends these methods, which currently assessments. However, have limitations, organizations recommend more advanced alternative approaches. In this study, we assessed validity nondetects. To identify most suitable nondetection, created virtual data conducted simulation studies. Based on both case studies, Maximum Likelihood Estimation (MLE) Robust Regression Order Statistics (ROS) were found best options. obtained from similar those commonly 1/2 Limit Detection (LOD) nondetection treatment. three compared various based root mean squared error. all studies same source, avoid heterogeneity. Across sample sizes rates, 95th percentile treatment similar. “lognormal maximum likelihood estimation” was not estimating mean. Risk should consider processing monitoring reduce uncertainty. Currently effective easy apply large datasets with rates <80%. required some circumstances, national guidelines needed regarding their use
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ژورنال
عنوان ژورنال: Food Science and Nutrition
سال: 2023
ISSN: ['2048-7177']
DOI: https://doi.org/10.1002/fsn3.3481