When multisource feedback instruments, for example, 360‐degree feedback tools, are validated, multilevel structural equation models are the method of choice to quantify the amount of reliability as well as convergent and discriminant validity. A non‐standard multilevel structural equation model that incorporates self‐ratings (level‐2 variables) and others’ ratings from different additional perspectives (level‐1 variables), for example, peers and subordinates, has recently been presented. In a Monte Carlo simulation study, we determine the minimal required sample sizes for this model. Model parameters are accurately estimated even with the smallest simulated sample size of 100 self‐ratings and two ratings of peers and of subordinates. The precise estimation of standard errors necessitates sample sizes of 400 self‐ratings or at least four ratings of peers and subordinates. However, if sample sizes are smaller, mainly standard errors concerning common method factors are biased. Interestingly, there are trade‐off effects between the sample sizes of self‐ratings and others’ ratings in their effect on estimation bias. The degree of convergent and discriminant validity has no effect on the accuracy of model estimates. The χ² test statistic does not follow the expected distribution. Therefore, we suggest using a corrected level‐specific standardized root mean square residual to analyse model fit and conclude with further recommendations for applied organizational research.

中文翻译：

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使用多级结构方程模型分析多源反馈：陷阱和来自仿真研究的建议。

当验证多源反馈工具（例如360度反馈工具）时，多级结构方程模型是量化可靠性，收敛性和判别有效性的一种选择方法。最近提出了一个非标准的多级结构方程模型，该模型结合了自评（级别2变量）和其他从不同的角度（级别1变量），例如同级和下属的评级。在蒙特卡洛模拟研究中，我们确定此模型所需的最小样本量。即使使用最小的100个自我评价的模拟样本量以及两个同级和下属的评级，模型参数也可以准确估算。对标准误的精确估计需要样本大小为400个自我评价或对等体和下属至少4个评价。但是，如果样本量较小，则主要是与常见方法因素有关的标准误差有偏差。有趣的是，在自我评价的样本量和其他人的评价对估计偏差的影响之间存在折衷效应。收敛性和判别有效性的程度对模型估计的准确性没有影响。的 收敛性和判别有效性的程度对模型估计的准确性没有影响。的 收敛性和判别有效性的程度对模型估计的准确性没有影响。的χ ²检验统计量不遵循预期分布。因此，我们建议使用校正后的特定于水平的标准化均方根残差来分析模型拟合，并为应用组织研究提供更多建议。