Scores on self-report questionnaires are often used in statistical models without accounting for measurement error, leading to bias in estimates related to those variables. While measurement error corrections exist, their broad application is limited by their simplicity (e.g., Spearman's correction for attenuation), which complicates their inclusion in specialized analyses, or complexity (e.g., latent variable modeling), which necessitates large sample sizes and can limit the analytic options available. To address these limitations, a flexible multiple imputation-based approach, called true score imputation, is described, which can accommodate a broad class of statistical models. By augmenting copies of the original dataset with sets of plausible true scores, the resulting set of datasets can be analyzed using widely available multiple imputation methodology, yielding point estimates and confidence intervals calculated with respect to the estimated true score. A simulation study demonstrates that the method yields a large reduction in bias compared to treating scores as measured without error, and a real-world data example is further used to illustrate the benefit of the method. An R package implements the proposed method via a custom imputation function for an existing, commonly used multiple imputation library (mice), allowing true score imputation to be used alongside multiple imputation for missing data, yielding a unified framework for accounting for both missing data and measurement error. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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一种用于解释心理测量误差的真实分数插补方法。

自我报告问卷的分数通常用于统计模型，而不考虑测量误差，导致与这些变量相关的估计存在偏差。虽然存在测量误差校正，但它们的广泛应用受到其简单性（例如，斯皮尔曼衰减校正）的限制，这使得它们在专门分析中的包含变得复杂，或者复杂性（例如，潜在变量建模），这需要大样本量并可能限制可用的分析选项。为了解决这些限制，描述了一种灵活的基于多重插补的方法，称为真实分数插补，它可以适应广泛的统计模型。通过使用可信的真实分数集来增强原始数据集的副本，可以使用广泛使用的多重插补方法来分析所得到的数据集集，从而产生点估计和相对于估计的真实分数计算的置信区间。模拟研究表明，与无误差测量的分数相比，该方法可以大大减少偏差，并且进一步使用真实世界的数据示例来说明该方法的好处。R 包通过现有常用多重插补库（小鼠）的自定义插补函数来实现所提出的方法，允许将真实分数插补与缺失数据的多重插补一起使用，从而产生一个统一的框架来计算缺失数据和测量误差。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。