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两阶段抽样对 F 统计量的影响AI 解读

The assumption of iid observations that underlies many statistical procedures is called into question when analyzing complex survey data. The population structure—particularly the existence of clusters in two-stage samples that usually exhibit positive intracluster correlation—invalidates the independence assumption. Kish and Frankel (1974) investigated the impact of this fact on regression analysis by using the standard sample-survey-theory framework; Campbell (1977) and…

两阶段抽样对 F 统计量的影响AI 解读

The assumption of iid observations that underlies many statistical procedures is called into question when analyzing complex survey data. The population structure-particularly the existence of clusters in two-stage samples that usually exhibit positive intracluster correlation-invalidates the independence assumption. Kish and Frankel (1974) investigated the impact of this fact on regression analysis by using the standard sample-survey-theory framework; Campbell (1977) and…

两阶段抽样对普通最小二乘方法的影响AI 解读

We look at the effect of intracluster correlation on standard procedures in linear regression. The ordinary least squares estimator, , of the coefficient vector performs well in most cases but the usual estimator of cov() and procedures based on this such as confidence intervals and hypothesis tests can be seriously misleading. The size of the effect, however, tends to be smaller than the corresponding effect on the variance of an estimated mean in two-stage sampling…

调查设计对回归分析的影响AI 解读

Summary Data arising from sample surveys are usually the result of complex survey design involving such techniques as stratification, multistage selection and the use of auxiliary information through unequal probability selection. These resulting data are often analysed using regression techniques without further regard to the sample design. This paper shows that, in general, ordinary least squares (OLS) regression will be biased in this situation even for large samples,…

指数分布均值标准估计量对污染的稳健性AI 解读

The performances of the standard estimators of the mean of an exponential distribution are evaluated when this basic distribution is contaminated by another of the same type. Surprisingly, perhaps, it is found that the sample mean is asymptotically fully efficient for the mean of a mixture. For small samples, on the other hand, a comparison of the two standard statistics with the appropriate optimal linear statistics in terms of the mean squared error and bias shows that for…