This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…

We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…

A strong relationship between creativity and major depression has been attested to in many past studies. These suggest a correlation between high creative propensity and the prevalence of depression as well as attribute the implementation of creative tasks in therapy with the facilitation and reduction of depressive symptoms. This article supports…

This paper briefly discusses four measurement challenges of data science or "big data" in educational assessments that are enabled by technology: 1. Dealing with change over time via time-based data. 2. How a digital performance space's relationships interact with learner actions, communications and products. 3. How layers of…

This paper provides a conceptual, empirical, and practical guide for estimating ordinal reliability coefficients for ordinal item response data (also referred to as Likert, Likert-type, ordered categorical, or rating scale item responses). Conventionally, reliability coefficients, such as Cronbach's alpha, are calculated using a Pearson…

This article shows how interfactor correlation is affected by error correlations. Theoretical and practical justifications for error correlations are given, and a new equivalence class of models is presented to explain the relationship between interfactor correlation and error correlations. The class allows simple, parsimonious modeling of error…

This paper describes an instrument designed for assessing learning outcomes in data management. In addition to assessment of student learning and ABET outcomes, we have also found the instrument to be effective for determining database placement of incoming information systems (IS) graduate students. Each of these three uses is discussed in this…

The importance of spatial ability for success in a variety of domains, particularly in science, technology, engineering, and mathematics (STEM), is widely acknowledged. Yet, students with high spatial ability are rarely identified, as Talent Searches for academically talented students focus on identifying high mathematical and verbal abilities.…

The rise in the prevalence of autism creates a need for a reliable and valid measure of attitudes towards autism. The current study describes the development of a brief 16-item measure of Societal Attitudes towards Autism (SATA) that exhibits sound psychometric properties and has a demonstrated ability to discriminate between expert and general…

Bifactor latent structures were introduced over 70 years ago, but only recently has bifactor modeling been rediscovered as an effective approach to modeling "construct-relevant" multidimensionality in a set of ordered categorical item responses. I begin by describing the Schmid-Leiman bifactor procedure (Schmid & Leiman, 1957) and highlight its…

A new class of parametric models that generalize the multivariate probit model and the errors-in-variables model is developed to model and analyze ordinal data. A general model structure is assumed to accommodate the information that is obtained via surrogate variables. A hybrid Gibbs sampler is developed to estimate the model parameters. To…

Schools often administer brief intelligence tests as the first step in the identification of students who are cognitively gifted. However, brief measures are often used without consideration of underlying constructs or the psychometric properties of the measures and without regard to the links between screening decisions and educational…

Mental chronometry (MC) studies cognitive processes measured by time. It provides an absolute, ratio scale. The limitations of instrumentation and statistical analysis caused the early studies in MC to be eclipsed by the "paper-and-pencil" psychometric tests started by Binet. However, they use an age-normed, rather than a ratio scale, which…

This article describes the development and the initial psychometric evaluation of the Social Issues Advocacy Scale in two studies. In the first study, an exploratory factor analysis (n = 278) revealed a four-factor scale, accounting for 71.4% of the variance, measuring different aspects of social issue advocacy: Political and Social Advocacy,…

A Chemistry Concept Reasoning Test was created and validated providing an easy-to-use tool for measuring conceptual understanding and critical scientific thinking of general chemistry models and theories. The test is designed to measure concept understanding comparable to that found in free-response questions requiring explanations over…