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- W2184896350 abstract "To warrant high quality of industrially produced food, for some of the ingredients we want to prove that the variation between samples does not exceed a certain limit. For this purpose, a sampling scheme with n samples analyzed k-times each is employed. Data from a corresponding experiment can be analyzed using a one-way random effects model. We are primarily interested in the variation of the random effect and want to show that this variation is sufficiently small. The objective of this paper is to determine the optimal combination of n and k such that the power of a corresponding test is sufficiently high while the total number of analyzes nk is minimized. To this end, we consider both the classical approximate upper confidence limit and a test based on generalized p-values, and we derive the distributions of the respective statistics. This allows us to determine the power of the corresponding tests by means of simulations. It is found that the approach based on generalized p-values is more powerful than the classical one. Finally, sampling recommendations are given based on prior estimates on the within and between samples variation." @default.
- W2184896350 created "2016-06-24" @default.
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- W2184896350 date "2011-01-01" @default.
- W2184896350 modified "2023-09-25" @default.
- W2184896350 title "Sample Size Determination for Testing the Variance Compound in a One-Way Random Effects Model" @default.
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- W2184896350 doi "https://doi.org/10.1080/16843703.2011.11673250" @default.
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