Mixtures experiments with mixing errors

Alaa Althubaiti, Alexander N. Donev

    Research output: Contribution to journalArticlepeer-review


    In mixture experiments the properties of mixtures are usually studied by mixing the amounts of the mixture components that are required to obtain the necessary proportions. This paper considers the impact of inaccuracies in discharging the required amounts of the mixture components on the statistical analysis of the data. It shows how the regression calibration approach can be used to minimize the resulting bias in the model and in the estimates of the model parameters, as well as to find correct estimates of the corresponding variances. Its application is made difficult by the complex structure of these errors. We also show how knowledge of the form of the model bias allows for choosing a manufacturing setting for a mixture product that is not biased and has smaller signal to noise ratio. © 2010 Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)692–700
    Number of pages9
    JournalJournal of Statistical Planning and Inference
    Issue number2
    Publication statusPublished - Feb 2011


    • Errors in variables
    • Regression calibration
    • Scheffé polynomial
    • Simplex lattice design
    • Weighted least squares


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