An analysis pipeline for estimating true intake from repeated measurements with random errors |
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Authors: | Seongil Jo Jeongseon Kim |
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Institution: | 1. Department of Statistics (Institute of Applied Statistics), Chonbuk National University, Jeonju-si, Jeollabuk-do, Republic of Korea;2. Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea |
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Abstract: | The accurate estimation of an individual's usual dietary intake is an important topic in nutritional epidemiology. This paper considers the best linear unbiased predictor (BLUP) computed from repeatedly measured dietary data and derives several nonparametric prediction intervals for true intake. However, the performance of the BLUP and the validity of prediction intervals depends on whether required model assumptions for the true intake estimation problem hold. To address this issue, the paper examines how the BLUP and prediction intervals behave in the case of a violation of model assumptions, and then proposes an analysis pipeline for checking them with data. |
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Keywords: | Analysis pipeline Best linear unbiased predictor Nonparametric prediction interval Repeated measurements Shrinkage estimator Usual dietary intake |
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