Explained Variance Measures for Multilevel Models
评估了多层模型中解释方差度量的准确性，通过蒙特卡洛模拟发现除第二层度量外，其他度量表现良好。
One challenge in using multilevel models is determining how to report the amount of explained variance. In multilevel models, explained variance can be reported for each level or for the total model. Existing measures have been based primarily on the reduction of variance components across models. However, these measures have not been reported consistently because they have some undesirable properties. The present study is one of the first to evaluate the accuracy of these measures using Monte Carlo simulations. In addition, a measure based on the full partitioning of variance in multilevel models was examined. With the exception of the Level 2 explained variance measure, all other measures performed well across our simulated conditions.