Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…

The aim of the present study was to examine Differential Distractor Functioning (DDF) as a means of improving the quality of a measure through understanding biased responses across groups. A DDF analysis could shed light on the potential sources of construct-irrelevant variance by examining whether the differential selection of incorrect choices…

In this study, we propose that the unique needs and characteristics of linguistic minorities should be considered throughout the test development process. Unlike most measurement invariance investigations in the assessment of linguistic minorities, which typically are conducted after test administration, we propose strategies that focus on the…

The purpose of this study was to enhance the meaning of the scores of an English-language test by developing performance levels and descriptors for reporting overall test performance. The levels and descriptors were intended to accompany the total scale scores of TOEFL Junior® Standard, an international test of English as a second/foreign…

This article presents a reanalysis of the data of 862 second and fourth graders collected in two previous studies, focusing on the influence of method (psychometric vs. chronometric) and stimulus type on the gender difference in mental-rotation accuracy. The children had to solve mental-rotation tasks with animal pictures, letters, or cube…

Test equating is a statistical procedure for adjusting for test form differences in difficulty in a standardized assessment. Equating results are supposed to hold for a specified target population (Kolen & Brennan, 2004; von Davier, Holland, & Thayer, 2004) and to be (relatively) independent of the subpopulations from the target population (see…

Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…

Measurement invariance is a common consideration in the evaluation of the validity and fairness of test scores when the tested population contains distinct groups of examinees, such as examinees receiving different forms of a translated test. Measurement invariance in polytomous items has traditionally been evaluated at the item-level,…

One of the most revolutionary advances in psychometric research during the last decades has been the systematic development of statistical models that allow for cognitive psychometric research (CPR) to be conducted. Many of the models currently available for such purposes are extensions of basic latent variable models in item response theory…

This investigation reports on the cross-cultural equivalence testing of the Self-Description Questionnaire II (short version; SDQII-S) for Indigenous and non-Indigenous Australian secondary student samples. A variety of statistical analysis techniques were employed to assess the psychometric properties of the SDQII-S for both the Indigenous and…

In this article, we emphasize that the Rasch model is not only very useful for psychological test calibration but is also necessary if the number of solved items is to be used as an examinee's score. Simplified proof that the Rasch model implies specific objective parameter comparisons is given. Consequently, a model check per se is possible. For…