Homoscedastic controlled calibration model
  In the context of the usual calibration model, we consider the case in which the independent variable is unobservable, but a pre-fixed value on its surrogate is available. Thus, considering controlled variables and assuming that the measurement errors have equal variances we propose a new calibration model. Likelihood based methodology is used to estimate the model parameters and the Fisher information matrix is used to construct a confidence interval for the unknown value of the regressor variable. A simulation study is carried out to asses the effect of the measurement error on the estimation of the parameter of interest. This new approach is illustrated with an example. 
Betsab\'e G. Blas Achic, M\^onica C. Sandoval and Olga Satomi Yoshida