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…

Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The…

Introduction: Item response theory (IRT) has received much attention in validation of assessment instrument because it allows the estimation of students' ability from any set of the items. Item response theory allows the difficulty and discrimination levels of each item on the test to be estimated. In the framework of IRT, item characteristics are…

Researchers have implemented inclusive research for over 30 years. This article describes how two research projects collaborated with researchers with disabilities and aligns the description with four attributes of inclusive research developed by a consensus of international experts with and without disabilities. The first project, the Person…

So far, modeling approaches for not-reached items have considered one single underlying process. However, missing values at the end of a test can occur for a variety of reasons. On the one hand, examinees may not reach the end of a test due to time limits and lack of working speed. On the other hand, examinees may not attempt all items and quit…

In this digital ITEMS module, Dr. Brian Leventhal and Dr. Allison Ames provide an overview of "Monte Carlo simulation studies" (MCSS) in "item response theory" (IRT). MCSS are utilized for a variety of reasons, one of the most compelling being that they can be used when analytic solutions are impractical or nonexistent because…

Validity evidence based on test content is critical to meaningful interpretation of test scores. Within high-stakes testing and accountability frameworks, content-related validity evidence is typically gathered via alignment studies, with panels of experts providing qualitative judgments on the degree to which test items align with the…

There has been increasing interest in applying integrative data analysis (IDA) to analyze data across multiple studies to increase sample size and statistical power. Measures of a construct are frequently not consistent across studies. This article provides a tutorial on the complex decisions that occur when conducting harmonization of measures…

Although Diagnostic Classification Models (DCMs) were introduced to education system decades ago, it seems that these models were not employed for the original aims upon which they had been designed. Using DCMs has been mostly common in analyzing large-scale non-diagnostic tests and these models have been rarely used in developing Cognitive…

In a signal detection theory (SDT) approach to multiple choice exams, examinees are viewed as choosing, for each item, the alternative that is perceived as being the most plausible, with perceived plausibility depending in part on whether or not an item is known. The SDT model is a process model and provides measures of item difficulty, item…

Measures that accurately capture the phenomenon are critical to research and practice in group work. The vast majority of group-related measures were developed using the reflective measurement model rooted in classical test theory (CTT). Depending on the construct definition and the measure's purpose, the reflective model may not always be the…

Heat and enthalpy are challenging topics for general chemistry students because they are conceptually complex and require avariety of quantitative problem-solving approaches. Expert chemists draw on conditional knowledge, deciding when and under what conditions a certain problem-solving approach should be used. Decision-based learning (DBL)…

In this article, we systematically introduce the just another Gibbs sampler (JAGS) software program to fit common Bayesian cognitive diagnosis models (CDMs) including the deterministic inputs, noisy "and" gate model; the deterministic inputs, noisy "or" gate model; the linear logistic model; the reduced reparameterized unified…

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

Attribute structure is an explicit way of presenting the relationship between attributes in diagnostic measurement. The specification of attribute structures directly affects the classification accuracy resulted from psychometric modeling. This study provides a conceptual framework for understanding misspecifications of attribute structures. Under…