Scoring high-dimensional assessments (e.g., > 15 traits) can be a challenging task. This paper introduces the multilabel neural network (MNN) as a scoring method for high-dimensional assessments. Additionally, it demonstrates how MNN can score the same test responses to maximize different performance metrics, such as accuracy, recall, or…

Although there exists an extensive amount of research on subscores and their properties, limited research has been conducted on categorical subscores and their interpretations. In this paper, we focus on the claim of Feinberg and von Davier that categorical subscores are useful for remediation and instructional purposes. We investigate this claim…

When no prior information of differential item functioning (DIF) exists for items in a test, either the rank-based or iterative purification procedure might be preferred. The rank-based purification selects anchor items based on a preliminary DIF test. For a preliminary DIF test, likelihood ratio test (LRT) based approaches (e.g.,…

Multidimensional achievement tests are recently gaining more importance in educational and psychological measurements. For example, multidimensional diagnostic tests can help students to determine which particular domain of knowledge they need to improve for better performance. To estimate the characteristics of candidate items (calibration) for…

Response styles pose great threats to psychological measurements. This research compares IRTree models and anchoring vignettes in addressing response styles and estimating the target traits. It also explores the potential of combining them at the item level and total-score level (ratios of extreme and middle responses to vignettes). Four models…

This study examined the widely used threshold of 0.2 for Yen's Q3, an index for violations of local independence. Specifically, a simulation was conducted to investigate whether Q3 values were related to the magnitude of bias in estimates of reliability, item parameters, and examinee ability. Results showed that Q3 values below the typical cut-off…

This study presents a generalized version of the residual differential item functioning (RDIF) detection framework in item response theory, named GRDIF, to analyze differential item functioning (DIF) in multiple groups. The GRDIF framework retains the advantages of the original RDIF framework, such as computational efficiency and ease of…

Large-scale standardized tests are regularly used to measure student achievement overall and for student subgroups. These uses assume tests provide comparable measures of outcomes across student subgroups, but prior research suggests score comparisons across gender groups may be complicated by the type of test items used. This paper presents…

The use of multistage adaptive testing (MST) has gradually increased in large-scale testing programs as MST achieves a balanced compromise between linear test design and item-level adaptive testing. MST works on the premise that each examinee gives their best effort when attempting the items, and their responses truly reflect what they know or can…

A conceptualization of multiple-choice exams in terms of signal detection theory (SDT) leads to simple measures of item difficulty and item discrimination that are closely related to, but also distinct from, those used in classical item analysis (CIA). The theory defines a "true split," depending on whether or not examinees know an item,…

The efficiency of cognitive component skills is typically assessed with speeded performance tests. Interpreting only effective ability or effective speed as efficiency may be challenging because of the within-person dependency between both variables (speed-ability tradeoff, SAT). The present study measures efficiency as effective ability…

This paper presents the item and test information functions of the Rank two-parameter logistic models (Rank-2PLM) for items with two (pair) and three (triplet) statements in forced-choice questionnaires. The Rank-2PLM model for pairs is the MUPP-2PLM (Multi-Unidimensional Pairwise Preference) and, for triplets, is the Triplet-2PLM. Fisher's…

Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…

When designing or modifying a test, an important challenge is controlling its speededness. To achieve this, van der Linden (2011a, 2011b) proposed using a lognormal response time model, more specifically the two-parameter lognormal model, and automated test assembly (ATA) via mixed integer linear programming. However, this approach has a severe…

Educational tests often have a cluster of items linked by a common stimulus ("testlet"). In such a design, the dependencies caused between items are called "testlet effects." In particular, the directional testlet effect (DTE) refers to a recursive influence whereby responses to earlier items can positively or negatively affect…