Development of an abbreviated Personal Globe Inventory using item response theory: The PGI-Short

The responses of 2813 individuals to the Personal Globe Inventory (Tracey, 2002) were examined with the goal of developing a shorter, yet valid version of the scale using item response theory to guide the process. A random sample of 1000 individuals was used to select the best items and then the remaining 1813 were used as a validation sample to examine psychometric properties. For items to be included in the shortened form, the option characteristic curves had to conform to theory and there could be no presence of differential item functioning across either gender or ethnicity. The best 80 items were retained forming the PGI-Short. This instrument demonstrated excellent reliability and adherence to a circular model, there was no differential item functioning across either gender or ethnicity. The PGI-Short was supported as an alternative to the fuller version of the PGI.     

在GLMM框架下统一GT与IRT

本文首次提出使用广义线性混合模型(Generalized Linear Mixed Model, GLMM)对概化理论(GT)和项目反应理论(IRT)进行统合,即在一次统计中就能同时获得GT和IRT所需要的估计结果。模拟研究结果显示：相比于传统的GT方差分量估计方法——期望均值平方(Expected Mean Squares, EMS),GLMM可以获得更准确的方差分量、G系数和Φ系数,而且GLMM获得的题目难度参数估计精度优于传统Rasch模型。实证研究展示GLMM在实际心理测量数据分析中的应用。     

The role of processes and contents in human memory: An item response theory approach

This study investigated the specificities and communalities of visuospatial and verbal memory contents, as well as short-term memory and working memory (STM and WM) processes with the use of Rasch models as an alternative to the previous studies based on the classical test theory. A sample of 547 undergraduate students executed four computerised tasks, each consisting of verbal-numeric WM, visuospatial WM, verbal-numeric STM, and visuospatial STM content. Confirmatory factor analyses indicated that visuospatial and verbal-numeric memory are distinct, but correlated variables. Findings also support a domain-general view of WM capacity distinct from domain-specific storage. With the use of Rasch models, our results confirm previous experimental, psychometric, and neuropsychological studies, highlighting that memory span tasks can be divided into separate subsystems for content and processes. This study also shows that better results are obtained when models with person parameter estimates (provided from Rasch models) are adopted, rather than summed raw scores.     

Rasch analysis and item reduction of the hypomanic personality scale

The aim of the current study was to reduce the number of items in the 48-item hypomanic personality scale (HPS) and determine whether a unidimensional scale of the hypomanic trait could be derived. Previously collected HPS data from University students (n = 318) were applied to the Rasch model (one-parameter item response theory). Overall scale and individual item fit statistics were used to judge fit to the model and item maps employed to determine coverage of the trait. Cronbach’s Alpha and correlations with other questionnaires pre- and post-item reduction were evaluated. Rasch analysis indicated that the original HPS was not unidimensional, had significant redundancy and differential item functioning by age and gender. An iterative process of item reduction produced a 20-item HPS (HPS-20) that retained the concepts of the original HPS and had excellent fit to the Rasch model (χ² p = 0.27). Unidimensionality of the HPS-20 was confirmed. The traditional psychometric properties of the HPS-20 and coverage of the underlying hypomanic construct were similar to the original. It was possible to derive a unidimensional measure of the hypomanic trait. Further use of the HPS-20 is encouraged as it may increase understanding of the risk factors for affective disorders.     

Measuring individual differences in sensitivities to basic emotions in faces

The assessment of individual differences in facial expression recognition is normally required to address two major issues: (1) high agreement level (ceiling effect) and (2) differential difficulty levels across emotions. We propose a new assessment method designed to quantify individual differences in the recognition of the six basic emotions, 'sensitivities to basic emotions in faces.' We attempted to address the two major assessment issues by using morphing techniques and item response theory (IRT). We used morphing to create intermediate, mixed facial expression stimuli with various levels of recognition difficulty. Applying IRT enabled us to estimate the individual latent trait levels underlying the recognition of respective emotions (sensitivity scores), unbiased by stimulus properties that constitute difficulty. In a series of two experiments we demonstrated that the sensitivity scores successfully addressed the two major assessment issues and their concomitant individual variability. Intriguingly, correlational analyses of the sensitivity scores to different emotions produced orthogonality between happy and non-happy emotion recognition. To our knowledge, this is the first report of the independence of happiness recognition, unaffected by stimulus difficulty.     

Gleaning Information for Cognitive Operations from Don’t Know Responses in Cognitive and Noncognitive Assessments

The Don’t Know (DK) response – taking the form of an omitted response or not-reached at the end of a cognitive test, or explicitly presented as a response option in a social survey – contains important information that is often overlooked. Direct psychometric modeling efforts for DK responses are few and far between. In this article, the linear logistic test model (LLTM) is proposed for delineating the impacts of cognitive operations for a test that contains DK responses. We assume that the DK response is a valid response. The assumption is reasonable for many situations, including low-stakes cognitive tests and attitudinal assessments. By extracting information embedded in the DK response, the method shows how DK can inform the latent construct of interest and the cognitive operations underlying the response to stimuli. Using a proven recoding scheme, the LLTM could be implemented through commonly used programs such as PROC GLIMMIX. Two simulation experiments to evaluate how well the parameters can be recovered were conducted. In addition, two real data examples, from a noncognitive test of health belief assessment and a cognitive test of knowledge in diabetes, are also presented as case studies to illustrate the LLTM for DK response.