整群抽样调查数据分析中应正确计算抽样误差

为了澄清整群抽样调查数据分析中正确计算抽样误差的必要性，以在某市15岁及以上人群中开展的一次两阶段整群抽样调查为例，分别采用适用于单纯随机抽样数据的方法和考虑了复杂抽样设计的方法对数据进行分析。结果显示，忽略对复杂抽样设计的考虑，不恰当的采用适用于单纯随机抽样数据的方法进行数据分析，不仅有可能大大低估样本统计量的抽样误差，在进行假设检验时，甚至会得到错误的结果，故正确分析和报告整群抽样调查数据的抽样误差是非常必要的。

Estimation of sampling error on data from cluster sample survey

To clarify the necessity of applying appropriate statistical methods to calculate sampling error from data of cluster sample survey,we take a two-stage cluster sample survey developed from a population aged 15 and over as example. We use statistical methods based on the assumption of simple random samples and methods considering complex sample design to analyze our data, respectively. Through comparison, we hope to show the potential effects of using improper statistical methods to estimate sampling error on parameter estimation and hypothesis testing. Using standard error algorithms based on the assumption of simple random samples, the standard errors calculated often underestimate sampling error and the hypothesis testing even gets wrong conclusion. When the statistical methods and statistics package for complex survey data are already available, it is necessary for us to use appropriate methods to analyze and report the sampling errors of data from cluster sample survey.