Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…

Researchers who work with ordinal rating scales sometimes encounter situations where the scale categories do not function in the intended or expected way. For example, participants' use of scale categories may result in an empirical difficulty ordering for the categories that does not match what was intended. Likewise, the level of distinction…

Human ratings are ubiquitous in creativity research. Yet, the process of rating responses to creativity tasks -- typically several hundred or thousands of responses, per rater -- is often time-consuming and expensive. Planned missing data designs, where raters only rate a subset of the total number of responses, have been recently proposed as one…

Data harmonization is an emerging approach to strategically combining data from multiple independent studies, enabling addressing new research questions that are not answerable by a single contributing study. A fundamental psychometric challenge for data harmonization is to create commensurate measures for the constructs of interest across…

Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimensional item response theory (MIRT) provides a unified framework and convenient statistical tool for item analysis, calibration, and scoring. However, the computational…

Computer-based and web-based testing have become increasingly popular in recent years. Their popularity has dramatically expanded the availability of response time data. Compared to the conventional item response data that are often dichotomous or polytomous, response time has the advantage of being continuous and can be collected in an…

Item-level fit analysis not only serves as a complementary check to global fit analysis, it is also essential in scale development because the fit results will guide item revision and/or deletion (Liu & Maydeu-Olivares, 2014). During data collection, missing response data may likely happen due to various reasons. Chi-square-based item fit…

Rater fit analyses provide insight into the degree to which rater judgments correspond to expected properties, as defined within a measurement framework. Parametric models such as the Rasch model provide a useful framework for evaluating rating quality; however, these models are not appropriate for all assessment contexts. The purpose of this…

Advancements in item response theory (IRT) have led to models for dual dependence, which control for cluster and method effects during a psychometric analysis. Currently, however, this class of models does not include one that controls for when the method effects stem from two method sources in which one source functions differently across the…

Psychometric modeling has become a frequently used statistical tool in research on scientific reasoning. We review psychometric modeling practices in this field, including model choice, model testing, and researchers' inferences based on their psychometric practices. A review of 11 empirical research studies reveals that the predominant…

With advances in technology, researchers and test developers are developing new item types to measure complex skills like problem solving and critical thinking. Analyzing such items is often challenging because of their complicated response patterns, and thus it is important to develop psychometric methods for practitioners and researchers to…

Traditional psychometric guidelines suggest that at least several hundred respondents are needed to obtain accurate parameter estimates under the Rasch model. However, recent research indicates that Rasch equating results in accurate parameter estimates with sample sizes as small as 25. Item parameter drift under the Rasch model has been…

Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…

Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:…

Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in…