Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…

Previous confirmatory factor analytic research that has examined the factor structure of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) has endorsed either higher order models or oblique factor models that tend to amalgamate both general factor and index factor sources of systematic variance. An alternative model that has not yet…

Both testlet design and hierarchical latent traits are fairly common in educational and psychological measurements. This study aimed to develop a new class of higher order testlet response models that consider both local item dependence within testlets and a hierarchy of latent traits. Due to high dimensionality, the authors adopted the Bayesian…

The statistical ramifications of using equal weights, as compared to regression-based differential weights, in the estimation of Wechsler Adult Intelligence Scale--Revised (WAIS-R) factor scores were explored using WAIS standardization data, based on 1,880 adults. Differences resulting from the two approaches were substantial, as is discussed.…

Premorbid intellectual function estimation is a crucial part of patient evaluation following a traumatic brain injury (TBI), especially in individuals with ADHD who are at higher risk for TBI compared to their non-ADHD peers. This study investigates the value of using regression-based estimates of intelligence for concurrently predicting measured…