In this study, the knowledge of estimation theory based on the corrected score (CS) approach is extended in a linear multivariate multiple regression model with heteroscedastic measurement errors (HMEs) and an unknown HME variance. The heteroscedasticity of the HME variance is assumed to be capable of being grouped into similar patterns and can be estimated by the pooled variance of the observations of the variable with HME in repeated measurements. The statistical properties of the proposed CS estimator are analytically investigated. The simulation results confirm the theoretical results. The proposed CS estimator outperforms the OLS estimator under all simulation conditions.
