Non-Gaussian Berkson Errors in Bioassay

Alaa Althubaiti, Alexander Donev (Editor)

    Research output: Book/ReportCommissioned report


    The experimental design plays an important role in every experimental study. However, if errors in the settings of the studied factors cannot be avoided, i.e. Berkson errors occur, the estimates of the model parameters may be biased and the variability in the study increased. Correction methods for the effect of Berkson errors are compared. The emphasis is on the study of correlated Berkson errors which follow non-Gaussian distribution as this appears to have been a neglected, yet important, area. We also examine independently distributed errors. It is shown that the regression calibration approach bias correction methods are useful whenthe Berkson errors are independent. However, when these errors are dependent, the newly proposed method B-SIMEX clearly outperforms the other methods.
    Original languageEnglish
    Place of Publication
    PublisherUniversity of Manchester
    Number of pages25
    Publication statusPublished - 12 May 2011

    Publication series

    NameResearch Report No. 2


    • Errors-in-variables, regression calibration, serial dilution designs, dilution errors, SIMEX, B-SIMEX


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