The Cross-Classified Mixed Effects Model (CCMEM) has been demonstrated to be a flexible framework for evaluating reliability by measurement specialists. Reliability can be estimated based on the variance components of the test scores. Built upon their accomplishment, this study extends the CCMEM to be used for evaluating validity evidence. Validity is viewed as the coherence among the elements of a measurement system. As such, validity can be evaluated by the user-reasoned desired or undesired fixed and random effects. Based on the data of ePIRLS 2016 Reading Assessment, we demonstrate how to obtain evidence for reliability and validity by CCMEM. We conclude with a discussion on the practicality and benefits of this validation method.

中文翻译：

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作为评估预期和不良影响的验证：来自交叉分类混合效应模型的见解

交叉分类混合效应模型 (CCMEM) 已被证明是测量专家评估可靠性的灵活框架。可以根据测试分数的方差分量来估计可靠性。基于他们的成就，本研究扩展了 CCMEM 以用于评估有效性证据。有效性被视为测量系统要素之间的一致性。因此，有效性可以通过用户推理的期望或不期望的固定和随机效应来评估。基于 ePIRLS 2016 Reading Assessment 的数据，我们演示了如何通过 CCMEM 获取信度和效度的证据。最后，我们讨论了这种验证方法的实用性和好处。