Testing for Block Effects in Regression Models Based on Survey Data
研究了在回归分析中使用整群或两阶段抽样数据时，如何检验回归扰动项中的区块内相关性，指出单侧拉格朗日乘子检验是局部最优不变检验，并比较了其与德宾-沃森检验的功效。
Abstract This article considers the problem of testing for intrablock or intracluster correlation in regression disturbances that may occur when cluster or two-stage sampling data is used in regression analysis. It points out that the one-sided Lagrange multiplier test is locally best invariant. An empirical power comparison suggests that if the block structure is known this test should be used. Otherwise the Durbin—Watson test provides a useful test, especially in large samples.