Using multidimensional item response theory to evaluate how response styles impact measurement

Multidimensional item response theory (MIRT) models for response style (e.g., Bolt, Lu, & Kim, 2014, Psychological Methods, 19, 528; Falk & Cai, 2016, Psychological Methods, 21, 328) provide flexibility in accommodating various response styles, but often present difficulty in isolating the effects of response style(s) from the intended substantive trait(s). In the presence of such measurement limitations, we consider several ways in which MIRT models are nevertheless useful in lending insight into how response styles may interfere with measurement for a given test instrument. Such a study can also inform whether alternative design considerations (e.g., anchoring vignettes, self-report items of heterogeneous content) that seek to control for response style effects may be helpful. We illustrate several aspects of an MIRT approach using real and simulated analyses.     

Rater Model Using Signal Detection Theory for Latent Differential Rater Functioning

Differential rater functioning (DRF) occurs when raters show evidence of exercising differential severity or leniency when scoring examinees within different subgroups. Previous studies of DRF have examined rater bias using manifest variables (e.g., use of covariates) to determine the subgroups. These manifest variables include gender and the ethnicity of the examinee. For example, a rater may score males more severely. Ideally, each rater’s severity should be invariant across subgroups. This study examines DRF in the context of latent subgroups that classify possible sources of DRF based on raters’ scoring behavior rather than manifest factors. An extension of the latent class signal detection theory (LC-SDT) model for identifying DRF is proposed and examined using real-world data and simulations. Results from real-world data show that the signal detection approach leads to an effective method to identify latent DRF. Simulations with varying sample sizes and conditions of rater precision were shown to recover parameters at an adequate level, supporting its use to identify latent DRF in large-scale data. These findings suggest that the DRF extension of the LC-SDT can be a useful model to examine characteristics of raters and add information that can aid rater training.     

Item response theory analyses of the Delis-Kaplan Executive Function System card sorting subtest

In the current study, we examined the dimensionality of the 16-item Card Sorting subtest of the Delis-Kaplan Executive Functioning System assessment in a sample of 264 native English-speaking children between the ages of 9 and 15 years. We also tested for measurement invariance for these items across age and gender groups using item response theory (IRT). Results of the exploratory factor analysis indicated that a two-factor model that distinguished between verbal and perceptual items provided the best fit to the data. Although the items demonstrated measurement invariance across age groups, measurement invariance was violated for gender groups, with two items demonstrating differential item functioning for males and females. Multigroup analysis using all 16 items indicated that the items were more effective for individuals whose IRT scale scores were relatively high. A single-group explanatory IRT model using 14 non-differential item functioning items showed that for perceptual ability, females scored higher than males and that scores increased with age for both males and females; for verbal ability, the observed increase in scores across age differed for males and females. The implications of these findings are discussed.     

Same face,same place,different memory: manner of presentation modulates the associative deficit in older adults

One of the more severe and consequential memory impairments experienced by older adults is the loss of the ability to form and remember associations. Although the associative deficit is often assumed to be unitary, memory episodes may contain different types of associations (e.g., item–item, item–context). Research in younger adults suggests that these different association types may involve different neural mechanisms. This raises the possibility that different association types are not equally affected by aging. In order to investigate this, the current study directly compared memory across item–item and item–context associations in younger and older adults by manipulating the manner of presentation of the associations. Results indicate that the associative deficit in aging is not uniform and that aging has a greater impact on item–context compared to item–item associations. The results have implications for theories of associative memory, age-related cognitive decline, and the functional organization of the medial temporal lobe in aging.     

Item Parameter Drift in Context Questionnaires from International Large-Scale Assessments

The purpose of the current study was to examine the impact of item parameter drift (IPD) occurring in context questionnaires from an international large-scale assessment and determine the most appropriate way to address IPD. Focusing on the context of psychometric and educational research where scores from context questionnaires composed of polytomous items were employed for the classification of examinees, the current research investigated the impacts of IPD on the estimation of questionnaire scores and classification accuracy with five manipulated factors: the length of a questionnaire, the proportion of items exhibiting IPD, the direction and magnitude of IPD, and three decisions about IPD. The results indicated that the impact of IPD occurring in a short context questionnaire on the accuracy of score estimation and classification of examinees was substantial. The accuracy in classification considerably decreased especially at the lowest and highest categories of a trait. Unlike the recommendation from literature in educational testing, the current study demonstrated that keeping items exhibiting IPD and removing them only for transformation were appropriate when IPD occurred in relatively short context questionnaires. Using 2011 TIMSS data from Iran, an applied example demonstrated the application of provided guidance in making appropriate decisions about IPD.     

Reliability and validity of the Basic Depression Questionnaire

Background/ObjectiveDepressive disorders have a high prevalence around the world. They present a great comorbidity with other disorders like anxiety, thereby making a differential diagnosis very difficult. The Basic Depression Questionnaire was designed to palliate this issue by isolating specific depression symptoms. Our aim is to study the reliability, factorial structure, and differential item functioning of this questionnaire. Method: The sample consisted of 1,397 adults without psychological problems (M_age = 29.76, SD = 11.25, 64.78% women) who completed the CBD. Results: We observed that none of the items presented differential functioning. A monofactorial structure was established. In this model a good fit was obtained by confirmatory factor analysis and a strict invariance by sex. The ordinal alpha was used to check the reliability and it fetched an index of .95. Conclusions: The Basic Depression Questionnaire has adequate psychometric properties. The absence of differential item functioning and the invariance by sex are guarantees of an adequate use to diagnose depression for men and women. So, its clinical use can help to differentiate between the specific diagnoses for depressive disorders and anxiety disorders.     

心理与教育测验中反应时模型应用的优势与举例

基于计算机形式的测验使得收集作答反应时信息成为可能,这些信息的有效利用对心理与教育测验的理论研究和实际应用产生了重大影响。首先,归纳并总结了测验中使用反应时信息的五大优势。其次,分别介绍了4种不同取向下较典型的反应时模型与模型特征,并分别进行评价。再次,较系统地梳理了反应时模型在实践中的应用,使读者了解反应时信息在测验中所发挥的作用。最后,探讨了未来将反应时应用于心理与教育测量领域的几个研究方向。     

Developing new online calibration methods for multidimensional computerized adaptive testing

Multidimensional computerized adaptive testing (MCAT) has received increasing attention over the past few years in educational measurement. Like all other formats of CAT, item replenishment is an essential part of MCAT for its item bank maintenance and management, which governs retiring overexposed or obsolete items over time and replacing them with new ones. Moreover, calibration precision of the new items will directly affect the estimation accuracy of examinees’ ability vectors. In unidimensional CAT (UCAT) and cognitive diagnostic CAT, online calibration techniques have been developed to effectively calibrate new items. However, there has been very little discussion of online calibration in MCAT in the literature. Thus, this paper proposes new online calibration methods for MCAT based upon some popular methods used in UCAT. Three representative methods, Method A, the ‘one EM cycle’ method and the ‘multiple EM cycles’ method, are generalized to MCAT. Three simulation studies were conducted to compare the three new methods by manipulating three factors (test length, item bank design, and level of correlation between coordinate dimensions). The results showed that all the new methods were able to recover the item parameters accurately, and the adaptive online calibration designs showed some improvements compared to the random design under most conditions.     

Non‐ignorable missingness item response theory models for choice effects in examinee‐selected items

Examinee‐selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non‐ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two‐dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non‐ignorable and to determine how to apply the new model to the data collected. Two follow‐up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non‐ignorable missing data were mistakenly treated as ignorable.