Abstract The purpose of this paper is to formally outline a sequence of propositions that describe the connections between five linearly additive measurement error models commonly used in disciplines from psychometrics and test theory to economics to epidemiology, and one new model formerly proposed in Kroc & Zumbo (2018). We show that although these models are deceptively similar in their general algebraic form, X = T + E , they have different error structures that both connect and distinguish them.

中文翻译：

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测量误差模型的跨学科观点和 X=T+E 的变化

摘要 本文的目的是正式概述一系列命题，这些命题描述了从心理测量学和测试理论到经济学再到流行病学等学科中常用的五种线性可加测量误差模型与先前在 Kroc & Zumbo 中提出的一个新模型之间的联系。 2018）。我们表明，尽管这些模型在其一般代数形式 X = T + E 上看似相似，但它们具有连接和区分它们的不同错误结构。