The Effect of Changes of Location on Least-Squares Estimators for Samples Stratified on the Dependent Variable
研究了因变量分层样本中最小二乘估计量对位置变化缺乏不变性的问题，发现当因变量原点远离均值时效率降低，并提出了两种不变估计量。
The consistent least-squares estimator, proposed by Jewell (1985) for linear regression with data arising from stratified samples, lacks invariance with respect to a change of location of the dependent variable. Simulation suggests that its efficiency is reduced when the origin of the dependent variable is far from its mean. This estimator can be made invariant to a change of location by specifying that the dependent variable is measured from the estimated population mean. Another similar invariant estimator is also suggested.