Should I Use Fixed or Random Effects?
Should I Use Fixed or Random Effects?
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DOI：
10.1017/psrm.2014.32
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发表时间：
2015-05-01
影响因子：
3.9
通讯作者：
Linzer, Drew A.
中科院分区：
文献类型：
--
作者：
Clark, Tom S.;Linzer, Drew A.
社会科学中的实证分析经常遇到聚集或分组的定量数据。为了解释群体水平的变化并提高模型拟合度，研究人员通常会指定固定效应模型或随机效应模型。但目前关于应首选哪种方法以及在什么条件下应首选的建议仍然含糊不清，有时甚至是矛盾的。本研究进行了一系列蒙特卡罗模拟，以评估应用研究中遇到的数据集的典型大小和类型的每个模型的推论中的偏差和方差造成的总误差。结果提供了数据集特征的类型，以帮助研究人员选择首选模型。
Empirical analyses in social science frequently confront quantitative data that are clustered or grouped. To account for group-level variation and improve model fit, researchers will commonly specify either a fixed-or random-effects model. But current advice on which approach should be preferred, and under what conditions, remains vague and sometimes contradictory. This study performs a series of Monte Carlo simulations to evaluate the total error due to bias and variance in the inferences of each model, for typical sizes and types of datasets encountered in applied research. The results offer a typology of dataset characteristics to help researchers choose a preferred model.