Smith Philip J, Hoaglin David C, Battaglia Michael P, Barker Lawrence
Centers for Disease Control and Prevention, National Immunization Program, 1600 Clifton Road, NE, Atlanta, GA 30333, USA.
Stat Med. 2003 Aug 15;22(15):2487-502. doi: 10.1002/sim.1471.
In complex probability sample surveys, numerous adjustments are customarily made to the survey weights to reduce potential bias in survey estimates. These adjustments include sampling design (SD) weight adjustments, which account for features of the sampling plan, and non-sampling design (NSD) weight adjustments, which account for non-sampling errors and other effects. Variance estimates prepared from complex survey data customarily account for SD weight adjustments, but rarely account for all NSD weight adjustments. As a result, variance estimates may be biased and standard confidence intervals may not achieve their nominal coverage levels. We describe the implementation of the bootstrap method to account for the SD and NSD weight adjustments for complex survey data. Using data from the National Immunization Survey (NIS), we illustrate the use of the bootstrap (i). for evaluating the use of standard confidence intervals that use Taylor series approximations to variance estimators that do not account for NSD weight adjustments, (ii). for obtaining confidence intervals for ranks estimated from weighted survey data, and (iii). for evaluating the predictive power of logistic regressions using receiver operating characteristic curve analyses that account for the SD and NSD adjustments made to the survey weights.
在复杂概率抽样调查中，通常会对调查权重进行大量调整，以减少调查估计中的潜在偏差。这些调整包括抽样设计（SD）权重调整，它考虑了抽样方案的特征；以及非抽样设计（NSD）权重调整，它考虑了非抽样误差和其他影响。根据复杂调查数据编制的方差估计通常会考虑SD权重调整，但很少考虑所有NSD权重调整。因此，方差估计可能存在偏差，标准置信区间可能无法达到其名义覆盖水平。我们描述了用于考虑复杂调查数据的SD和NSD权重调整的自助法的实施。使用来自国家免疫调查（NIS）的数据，我们说明了自助法的用途：（i）用于评估使用泰勒级数近似对方差估计量进行估计的标准置信区间的使用情况，这些方差估计量未考虑NSD权重调整；（ii）用于获得根据加权调查数据估计的秩的置信区间；以及（iii）用于使用考虑了对调查权重进行的SD和NSD调整的接收者操作特征曲线分析来评估逻辑回归的预测能力。
