Structural comparative calibration using the EM algorithm

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Abstract
The problem of comparing the linear calibration equations of several measuring methods, each designed to measure the same characteristic on a common group of individuals, is discussed. We consider the factor analysis version of the model and propose to estimate the model parameters using the EM algorithm. The equations that define the ‘M’ step are simple to implement and computationally in expensive, requiring no additional maximization procedures. The derivation of the complete data log-likelihood function makes it possible to obtain the expected and observed information matrices for any number p(> 3) of instruments in closed form, upon which large sample inference on the parameters can be based. Re-analysis of two actual data sets is presented.