Applications of polytomous IRT models in applied fields (e.g., health, education, psychology) are abound. However, little is known about the impact of the number of categories and sample size requirements for precise parameter recovery. In a simulation study, we investigated the impact of the number of response categories and required sample size…

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…

Often, important decisions regarding accountability and placement of students in performance categories are made on the basis of test scores generated from tests, therefore, it is important to evaluate the validity of the inferences derived from test results. One of the threats to the validity of such inferences is aberrant responding. Several…

Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…

There is an increasing demand for assessments that can provide more fine-grained information about examinees. In response to the demand, diagnostic measurement provides students with feedback on their strengths and weaknesses on specific skills by classifying them into mastery or nonmastery attribute categories. These attributes often form a…

MOCCA is an online assessment of inferential reading comprehension for students in 3rd through 6th grades. It can be used to identify good readers and, for struggling readers, identify those who overly rely on either a Paraphrasing process or an Elaborating process when their comprehension is incorrect. Here a propensity to over-rely on…

Likert-type rating scales are still the most widely used method when measuring psychoeducational constructs. The present study investigates a long-standing issue of identifying the optimal number of response categories. A special emphasis is given to categorical data, which were generated by the Item Response Theory (IRT) Graded-Response Modeling…

Within the framework of item response theory (IRT), there are two recent lines of work on the estimation of classification accuracy (CA) rate. One approach estimates CA when decisions are made based on total sum scores, the other based on latent trait estimates. The former is referred to as the Lee approach, and the latter, the Rudner approach,…

Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be "tailored" to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends…

The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in noncompensatory multidimensional item response models using dimensionality assessment procedures based on DETECT (dimensionality evaluation to enumerate contributing traits) and NOHARM (normal ogive harmonic analysis robust method). Five…

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…

This study investigated the Type I error rate and power of the multivariate extension of the S - [chi][squared] statistic using unidimensional and multidimensional item response theory (UIRT and MIRT, respectively) models as well as full-information bifactor (FI-bifactor) models through simulation. Manipulated factors included test length, sample…

This article introduces two new classification consistency indices that can be used when item response theory (IRT) models have been applied. The new indices are shown to be related to Rudner's classification accuracy index and Guo's classification accuracy index. The Rudner- and Guo-based classification accuracy and consistency indices are…

Computer-adaptive classification tests focus on classifying respondents in different proficiency groups (e.g., for pass/fail decisions). To date, adaptive classification testing has been dominated by research on dichotomous response formats and classifications in two groups. This article extends this line of research to polytomous classification…

This study elaborates the Rasch differential item functioning (DIF) model formulation under the marginal maximum likelihood estimation context. Also, the Rasch DIF model performance was examined and compared with the Mantel-Haenszel (MH) procedure in small sample and short test length conditions through simulations. The theoretically known…