title: Robust bivariate errors-in-variables regression and outlier detection.
abstract: A bivariate regression model is introduced where both variables are subject to error. The structural regression line is equivariant against interchanging coordinates and permits bivariate calibration, i.e. the prediction of one variable by means of the other. Maximum likelihood and robust parameter are estimated, based on order statistics. Residual analysis and outlier detection are performed. The model is applied to the comparison of clinical chemical analytical methods.
authors.affiliation: Abteilung für Medizinische Statistik, Universität Heidelberg, Klinikum Mannheim, Germany.
authors.forename: U
authors.initials: U
authors.lastname: Feldmann
mesh_terms: D006400:Hematocrit; D006801:Humans; D015233:Models, Statistical; D012044:Regression Analysis