Estimation of Within Model Parameters in Regression Models With a Nested Error Structure
研究了嵌套误差结构下回归参数的估计问题，给出了普通最小二乘估计为一致最小方差无偏估计的充分条件，并提出了三种替代估计方法进行比较。
Abstract Restricted randomizations, similar to those in split-plot type experiments, often are adapted to assign quantitative treatment factors to experimental units. Such restrictions result in the experiment having a nested error structure. Sufficient conditions are presented under which ordinary least squares (OLS) estimates of regressor parameters are uniformly minimum variance unbiased (UMVU). If one designs experiments so that these conditions are satisfied, the analysis is straightforward and easy. When these conditions are not met, three different estimators of nested regressor parameters are suggested and compared.