The article discusses a method to estimate linear regression models when the measurements of independent variables have varying errors. By using a new estimator called HEIV, which considers the different variances of measurement errors, more efficient results can be obtained compared to traditional methods. Simulations suggest that this new approach can lead to significant improvements in practice. The HEIV estimator is easy to calculate using standard regression software.