Covariate-Adjusted Regression Models

The covariate-adjusted regression model was proposed by Sent(?)rk and M(?)ller in order to analyze the relationship between plasma fibrinogen concentration and serum transferrin in hemodialysis patients. The predictor and response variables in the model are not directly visible, but can be observed by some measured covariates after the distortion of the data. Mainly used in finance, economics, clinical medicine, sociology and other fields. because of its important reality Which is widely concerned at home and abroad. In this paper, the model conditions are weakened and the new estimators are constructed under the condition that the results are more lenient than the previous ones. The statistical properties of the parameters in the linear covariance adjustment model are proved, which is mainly the consistency and progressive normality under the condition that the results are more lenient than the previous results. The simulation and real data analysis gave a further assessment of the performance of the method.