An Isotonic Partial Credit Model for Ordering Subjects on the Basis of Their Sum Scores

In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable. However, the PCM is very restrictive with respect to the constraints that it imposes on the data. In this paper, sufficient conditions for the stochastic ordering of subjects by their sum score are obtained. These conditions define the isotonic (nonparametric) PCM model. The isotonic PCM is more flexible than the PCM, which makes it useful for a wider variety of tests. Also, observable properties of the isotonic PCM are derived in the form of inequality constraints. It is shown how to obtain estimates of the score distribution under these constraints by using the Gibbs sampling algorithm. A small simulation study shows that the Bayesian p-values based on the log-likelihood ratio statistic can be used to assess the fit of the isotonic PCM to the data, where model-data fit can be taken as a justification of the use of the sum score to order subjects.     

Optimal Scores: An Alternative to Parametric Item Response Theory and Sum Scores

Psychometrika - The aim of this paper is to discuss nonparametric item response theory scores in terms of optimal scores as an alternative to parametric item response theory scores and sum scores....     

多维题组效应Rasch模型

首先, 本文诠释了“题组”的本质即一个存在共同刺激的项目集合。并基于此, 将题组效应划分为项目内单维题组效应和项目内多维题组效应。其次, 本文基于Rasch模型开发了二级评分和多级评分的多维题组效应Rasch模型, 以期较好地处理项目内多维题组效应。最后, 模拟研究结果显示新模型有效合理, 与Rasch题组模型、分部评分模型对比研究后表明：(1)测验存在项目内多维题组效应时, 仅把明显的捆绑式题组效应进行分离而忽略其他潜在的题组效应, 仍会导致参数的偏差估计甚或高估测验信度; (2)新模型更具普适性, 即便当被试作答数据不存在题组效应或只存在项目内单维题组效应, 采用新模型进行测验分析也能得到较好的参数估计结果。     

Societal QOL is More than the Sum of QOL of Individuals: The Whole is Greater than the Sum of the Parts

I submit that we are too focused on individual-level happiness research at the expense of societal level QOL research. That is, societal QOL cannot be simply treated as the sum of the happiness of individual citizens. In making this assertion I review and discuss Abott Ferris’ latest book: Approaches to Improving the Quality of Life (published by Springer, 2010).     

Optimal Designs for the Rasch Model

In this paper, optimal designs will be derived for estimating the ability parameters of the Rasch model when difficulty parameters are known. It is well established that a design is locally D-optimal if the ability and difficulty coincide. But locally optimal designs require that the ability parameters to be estimated are known. To attenuate this very restrictive assumption, prior knowledge on the ability parameter may be incorporated within a Bayesian approach. Several symmetric weight distributions, e.g., uniform, normal and logistic distributions, will be considered. Furthermore, maximin efficient designs are developed where the minimal efficiency is maximized over a specified range of ability parameters.     

无领导小组讨论的多侧面Rasch模型应用*

采用项目反应理论(IRT)的多侧面Rasch模型(MFRM),分析评价中心技术中无领导小组讨论(LGD)的测评结果,探讨被试能力水平、评委评分宽严度、评分内部一致性、维度难度和评定等级等问题,进而讨论各种偏差。通过 MFRM 分析人事测评结果,可深入了解被试能力的真实差异、甑别维度难度、探查测评误差源,从而完善测评试题编制、评估或诊断评委合格性、提高测评维度与测评目的匹配性,为拓展项目反应理论在人事测评中的应用提供独特视角。     

K-means、潜在类别模型和混合Rasch模型的比较

基于模拟研究比较了K-means方法、潜在类别模型和混合Rasch模型在二分外显变量情境下的聚类效果.结果表明：（1）潜在类别数量、变量数量、样本量、样本平衡和变量间相关对K-means方法、潜在类别模型和混合Rasch模型的分类准确性均有影响且因素间的交互作用存在;（2）除了在2个潜在类别的样本不平衡条件下K-means方法表现较差外,在其他条件下与潜在类别模型和混合Rasch模型的表现相当;（3）混合Rasch模型的分类一致性在2个潜在类别的情境下要好于潜在类别模型,但是在4个潜在类别的情境下要差于潜在类别模型.     

Stochastic Ordering Of the Latent Trait by the Sum Score Under Various Polytomous IRT Models

The sum score is often used to order respondents on the latent trait measured by the test. Therefore, it is desirable that under the chosen model the sum score stochastically orders the latent trait. It is known that unlike dichotomous item response theory (IRT) models, most polytomous IRT models do not imply stochastic ordering. It is unknown, however, (1) whether stochastic ordering is often or rarely violated and (2) whether violations yield a serious problem for practical data analysis. These are the central issues of this paper. First, some unanswered questions that pertain to polytomous IRT models implying stochastic ordering were investigated. Second, simulation studies were conducted to evaluate stochastic ordering in practical situations. It was found that for most polytomous IRT models that do not imply stochastic ordering, the sum score can be used safely to order respondents on the latent trait.The author would like to thank Klaas Sijtsma for commenting on earlier drafts of this paper.     

Confidence Distribution for the Ability Parameter of the Rasch Model

Psychometrika - In this paper, we consider the Rasch model and suggest novel point estimators and confidence intervals for the ability parameter. They are based on a proposed confidence...     

心理科学领域内的客观测量——Rasch模型之特点及发展趋势

Rasch模型是在国外学术界受到广泛关注和深入研究的一个潜在特质模型。该模型为解决心理科学领域内测量的客观性问题提供了一个可行性很高的解决方案。而国内关于Rasch模型的理论探讨和应用研究却并不多见。不同于一般项目反应理论, Rasch模型要求所收集的数据必须符合模型的先验要求, 而不是使用不同的参数去适应数据的特点。Rasch模型的主要特点(包括个体与题目共用标尺、线性数据、参数分离)确保了客观测量的实现。未来关于Rasch模型的研究方向包括多维度Rasch模型、测验的等值与链接、计算机自适应性考试, 大型应用测量系统(比如Lexile系统)等等。     

多面Rasch模型理论及其在结构化面试中的应用

针对影响面试效度的各种误差来源,该文引入了一种新颖的面试结果处理方法：多面Rasch模型。这一模型在结构化面试中的应用不但有利于有效测量被试的能力水平,而且为识别问题评委、进一步完善评分规则、实现面试等值等问题都提供了全新的解决思路。文章在对结构化面试信、效度研究进展进行综述的基础上,介绍了多面Rasch模型的理论及其在结构化面试中的应用框架。     

协单参数单维度Rasch模型的优势与意义

相比多参数多维度IRT模型通过增加参数的方式来提升模型拟合度和解释度，Rasch模型流派强调“理论驱动研究”和“数据符合模型”，推崇单参数单维度的测量模型能最大限度地减少额外因素对真实测量目的的影响和干扰，从而保证测量的客观性和准确性。Rasch模型关注测量目标与测量工具的对应关系，它的“简单”特性有助于研究者更准确地评估和解释被测目标与测量工具间的适配性，且在将非线性数据转化为等距数据时具有天然的优势。     

多面Rasch模型在结构化面试中的应用

使用项目反应理论中的多面Rasch模型,对66名考生在结构化面试中的成绩进行分析,剔除了由于评委等具体测量情境因素引入的误差对原始分数的影响,得到考生的能力估计值以及个体水平的评分者一致性信息。对基于考生能力估计值和考生面试分得到的决策结果进行比较,发现测量误差的确对决策造成影响,对个别考生的影响甚至相当巨大。进一步使用Facets偏差分析以及评委宽严程度的Facets分析追踪误差源。结果表明,将来自不同面试组的被试进行面试原始成绩的直接比较,评委的自身一致性和评委彼此之间在宽严程度上的差异均将导致误差。研究表明,采用Facets的考生能力估计值作为决策的依据将提高选拔的有效性。同时,Facets分析得到的考生个体层次的评分者一致性指标,以及评委与考生的偏差分析等研究结果还可以为面试误差来源的定位提供详细的诊断信息     

Applying the Mixed Rasch Model to the Runco Ideational Behavior Scale

Previous research using creativity assessments has used latent class models and identified multiple classes (a 3-class solution) associated with various domains. This study explored the latent class structure of the Runco Ideational Behavior Scale, which was designed to quantify ideational capacity. A robust state-of the-art technique called the Mixed Rasch Model (MRM) was utilized with a sample of 765 Turkish middle school students. Consistent with previous studies, 3 clear latent classes were found in this study. Class 1 represents the regular ideators class, Class 2 the idea-producers class, and Class 3 the idea-averters class. In this study the 3-class solution represents 3 different skills, rather than 3 different domains. This study showed a promising application of MRMs as an alternative to the latent class analysis (LCA) technique for researchers in the field. The study also provided further evidence for the multiple class structure found in previous creativity assessments.     

纵向Rasch模型在大学新生适应性追踪研究中的应用

对1952名大学新生进行适应性调查,其中285人接受了2次以上的追踪调查,所得的多级评分重复测量数据采用纵向Rasch模型进行统计分析。研究应用SAS的GLIMMIX过程对多层Rasch模型参数估计作了新的尝试。结果表明：（1）新生在第一学年内,学习和情绪适应总体呈上升趋势,人际适应呈下降趋势;（2）不同个体入学时的适应状况差异显著,但是随时间变化的趋势、快慢相同;（3）学习适应分量表的项目稳定性较好,而人际、情绪适应的部分项目难度存在时间效应。研究结果对新生辅导具有启示意义     

应用Rasch模型分析Rosenberg自尊量表

采用Rosenberg自尊量表(RSES)对425名在校大学生进行施测,应用项目反应理论的Rasch模型对项目指标进行分析及DIF检验。结果表明,Rosenberg自尊量表具有单维性,量表的信度为0.84; 除项目8以外,其他项目拟合指标良好,较适用来区分中等及偏低自尊水平的个体,项目功能差异检验发现在项目1和项目5上存在DIF,表现为男生自尊水平要高于女生。相对于经典测量理论,应用Rasch模型分析Rosenberg自尊量表具有优势,为进一步的完善和使用该自尊量表提供依据。     

Fitting the Normal-Ogive Factor Analytic Model to Scores on Tests

This article (a) describes how McDonald's nonlinear factor analytic approach to the normal ogive curve can be used to factor analyse total test scores, (b) discusses the conditions in which this model is more appropriate than the widely used linear model, and (c) illustrates the applicability of both models using an empirical example. The rationale for the described procedure is that the test scores are simple sums of binary item responses whose item characteristic curves are adequately represented by normal ogives. The results obtained in the empirical example are meaningful and informative, and agree with the results obtained at the item level.     

Clinical Use of the Five-Factor Model: An Introduction

In the past decade, clinical psychologists have developed a renewed appreciation of the value of assessment. At the same time, personality psychologists have come to agree on a fundamental taxonomy of personality traits, the five-factor model. Articles in this special series describe the model and its measurement and discuss applications in three different settings: general clinical practice, a sexual behaviors consultation unit, and a behavioral medicine clinic. This introduction raises questions about the use of personality profiles in psychodiagnosis, the range of applicability of the five-factor model, the utility of personality feedback in psychotherapy, the stability of personality scores among psychotherapy patients, and the feasibility of using personality scores to select optimal forms of treatment. This special series is intended to stimulate research on such topics.     

Construction of a depression scale with the Rasch model

This study examines the psychometric properties of a depression questionnaire. The goal was to improve the technical quality of traditional measures of depression in Spanish youth. 310 participants, aged 18-24 years, filled in the self-report questionnaire. The data were analyzed by means of the Rasch model. Results show that model fit, average item reliability (.97), and average person reliability (.88) are high. After deleting four indicators showing misfit and 12 showing sex bias, the resulting scale measures clinical depression objectively. Using this scale, the expected sex-related differences are found.