The PROC NLMIXED procedure in Statistical Analysis System can be used to estimate parameters of item response theory (IRT) models. The data for this procedure are set up in a particular format called the "long format." The long format takes a substantial amount of time to execute the program. This article describes a format called the "wide…

An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…

Computerized adaptive testing (CAT) enables efficient and flexible measurement of latent constructs. The majority of educational and cognitive measurement constructs are based on dichotomous item response theory (IRT) models. An integral part of developing various components of a CAT system is conducting simulations using both known and empirical…

The models used in this article are secondary dimension mixture models with the potential to explain differential item functioning (DIF) between latent classes, called latent DIF. The focus is on models with a secondary dimension that is at the same time specific to the DIF latent class and linked to an item property. A description of the models…

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…

Polynomial loglinear models for one-, two-, and higher-way contingency tables have important applications to measurement and assessment. They are essentially regarded as a smoothing technique, which is commonly referred to as loglinear smoothing. A SAS IML (SAS Institute, 2002a) macro was created to implement loglinear smoothing according to…

Models for measuring individual response precision have been proposed for binary and graded responses. However, more continuous formats are quite common in personality measurement and are usually analyzed with the linear factor analysis model. This study extends the general Gaussian person-fluctuation model to the continuous-response case and…

SEMModComp, a software package for conducting likelihood ratio tests for mean and covariance structure modeling is described. The package is written in R and freely available for download or on request.

Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…

Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…

To rule out the need for a two-parameter item response theory (IRT) model during item analysis by Rasch models, it is important to check the Rasch model's assumption that all items have the same item discrimination. Biserial and polyserial correlation coefficients measuring the association between items and restscores are often used in an informal…

In this study, all the advantages of slope parameters, random weights, and latent regression are acknowledged when dealing with component and composite items by adding slope parameters and random weights into the standard item response model with internal restrictions on item difficulty and formulating this new model within a multilevel framework…

The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…

This study examined how well current software implementations of four polytomous item response theory models fit several multiple-choice tests. The main conclusion is that fitting polytomous item response models to multiple-choice item responses is more complex than fitting the three-parameter logistic model to dichotomously scored responses. (SLD)