Abstract
The main goal of this chapter is to study inference for models used in the detection of analytical bias in the comparison of two or more measurement methods. We embrace a functional errors-in-variables regression model with an EM-type algorithm for computing maximum likelihood estimates and to obtain consistent estimators for the asymptotic covariance matrix of the maximum likelihood estimators. Wald type statistics are proposed for testing hypothesis related to the bias of the analytical methods with the asymptotic chi-square distribution, which guarantees correct asymptotic significance levels. Some approaches specific for the two methods comparison problem are not directly extendable to this more general situation.
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