The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach. We provide a background on GEEs, discuss why it is appropriate for the analysis of clustered data, and provide worked examples using both continuous and binary outcomes. Comparisons are made between GEEs, multilevel models, and ordinary least squares results to highlight similarities and differences between the approaches. Detailed walkthroughs are provided using both R and SPSS Version 26.

中文翻译：

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使用广义估计方程分析横截面聚类数据

聚类数据的存在在社会行为科学中很常见。一种专门处理聚类数据但在教育中很少使用的方法是广义估计方程 (GEE) 方法。我们提供了 GEE 的背景，讨论了为什么它适合分析聚类数据，并提供使用连续和二元结果的工作示例。在 GEE、多级模型和普通最小二乘法结果之间进行比较，以突出这些方法之间的异同。使用 R 和 SPSS 版本 26 提供了详细的演练。