BMC Med Res Methodol. 2012 Jun 11;12:74. doi: 10.1186/1471-2288-12-74.
Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related) Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires.
Scalability of data from 1) a cross-sectional health survey (the Scottish Health Education Population Survey) and 2) a general population birth cohort study (the National Child Development Study) illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale.
After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items) we show that all items from the 12-item General Health Questionnaire (GHQ-12)--when binary scored--were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech's "well-being" and "distress" clinical scales). An illustration of ordinal item analysis confirmed that all 14 positively worded items of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) met criteria for the monotone homogeneity model but four items violated double monotonicity with respect to a single underlying dimension.Software availability and commands used to specify unidimensionality and reliability analysis and graphical displays for diagnosing monotone homogeneity and double monotonicity are discussed, with an emphasis on current implementations in freeware.
Mokken 刻度技术是一种有用的工具，适用于希望构建单维测试或使用包含多个二项或多项选择题的问卷的研究人员。当意图通过简单地添加项目反应值来评分潜在的潜在特征时，该方法提供的随机累积刻度模型是理想的。根据我们的经验，Mokken 模型似乎不如例如（相关）Rasch 模型那么知名，但在当代临床研究和公共卫生领域的使用越来越多。Mokken 的方法是 Guttman 刻度的推广，可以帮助确定测试或量表的维度，并能够在不依赖 Cronbach 的 alpha 的情况下考虑可靠性。本文提供了一个实用指南，介绍了这种非参数项目反应理论方法在健康和幸福感问卷的实证研究中的应用和解释。
来自 1）横断面健康调查（苏格兰健康教育人口调查）和 2）一般人群出生队列研究（国家儿童发展研究）的数据的可刻度性分别说明了二项和多项项目的方法和建模步骤。分析的问卷数据包括根据推荐用于筛选应用的二进制重新编码对 12 项一般健康问卷（GHQ-12）的反应，以及对沃里克-爱丁堡心理健康量表的有序/多项反应。
在我们通过措辞选择项目的初始分析示例（六阳性对六阴性项目）之后，我们表明，所有 12 项一般健康问卷（GHQ-12）的项目（二进制评分）根据双单调模型，在两个包含每个六个项目的短量表中是可刻度的（Bech 的“幸福感”和“痛苦”临床量表）。有序项目分析的说明证实，沃里克-爱丁堡心理健康量表（WEMWBS）的所有 14 个正向项目都符合单调同质性模型的标准，但四个项目在单一潜在维度方面违反了双单调性。讨论了软件可用性和用于指定单维性和可靠性分析的命令以及用于诊断单调同质性和双单调性的图形显示，重点是免费软件中的当前实现。
