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. 2014 Jun;26(3):171-7.
doi: 10.3969/j.issn.1002-0829.2014.03.010.

Item response theory for measurement validity

Frances M Yang  1 , Solon T Kao  2
Affiliations

Item response theory for measurement validity

Frances M Yang et al. Shanghai Arch Psychiatry. 2014 Jun.

Abstract
in English, Chinese

Item response theory (IRT) is an important method of assessing the validity of measurement scales that is underutilized in the field of psychiatry. IRT describes the relationship between a latent trait (e.g., the construct that the scale proposes to assess), the properties of the items in the scale, and respondents' answers to the individual items. This paper introduces the basic premise, assumptions, and methods of IRT. To help explain these concepts we generate a hypothetical scale using three items from a modified, binary (yes/no) response version of the Center for Epidemiological Studies-Depression scale that was administered to 19,399 respondents. We first conducted a factor analysis to confirm the unidimensionality of the three items and then proceeded with Mplus software to construct the 2-Parameter Logic (2-PL) IRT model of the data, a method which allows for estimates of both item discrimination and item difficulty. The utility of this information both for clinical purposes and for scale construction purposes is discussed.

项目反应理论（Item response theory, IRT）是用来评估精神病学领域那些尚未被充分使用的测量量表效度一种重要方法。 IRT描述了潜在心理特征（例如，该量表拟评估心理问题的架构）、量表中各项目的属性、以及被测试者对各项目应答之间的关系。本文介绍了IRT的基本前提，假设和方法。为了帮助解释这些概念，我们依据流行病学调查中心抑郁量表修订版中三个答案为是/否二分类选项的问题制定了一个假设的量表。流行病学调查中心抑郁量表已经用于19,399被测试者。我们首先用因子分析确认这三个项目的单维性，然后用Mplus软件建立2-Parameter Logic (2-PL) IRT模型，这是一种用来评估量表中各项目两两差异和项目难度的方法。本文将就这些分析结果的临床意义和在量表结构中的用途展开讨论。

Keywords: CES-D; Health and Retirement Study; Item Response Theory; Mplus; latent variable modeling.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1. Item characteristic curves for the items in the ‘Lack of Positive Affect’ scale
Figure 2
Figure 2. Item information curves for three items in the ‘Lack of Positive Affect’ scale
Figure 3
Figure 3. Test information curve of the ‘Lack of Positive Affect’ scale
See this image and copyright information in PMC

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