This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…

Normative studies are needed to obtain norms for comparing individuals with the reference population on relevant clinical or educational measures. Norms can be obtained in an efficient way by regressing the test score on relevant predictors, such as age and sex. When several measures are normed with the same sample, a multivariate regression-based…

The current study aims to evaluate the performance of three non-IRT procedures (i.e., normal approximation, Livingston-Lewis, and compound multinomial) for estimating classification indices when the observed score distribution shows atypical patterns: (a) bimodality, (b) structural (i.e., systematic) bumpiness, or (c) structural zeros (i.e., no…

This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…

This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…

In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science self-efficacy, and weekly…

When item scores are ordered categorical, categorical omega can be computed based on the parameter estimates from a factor analysis model using frequentist estimators such as diagonally weighted least squares. When the sample size is relatively small and thresholds are different across items, using diagonally weighted least squares can yield a…

Policymakers have grown increasingly interested in how experimental results may generalize to a larger population. However, recently developed propensity score-based methods are limited by small sample sizes, where the experimental study is generalized to a population that is at least 20 times larger. This is particularly problematic for methods…

As the theme of the 2022 annual meeting of the American Education Research Association, cultivating equitable education systems has gained renewed attention amid an increasingly diverse society. However, systemic inequalities persist for traditionally underserved student populations. As a way to better address diverse students' needs, it is of…

Rudner (2001, 2005) described an expected classification accuracy index for determining the asymptotic expectation of accuracy of classifications of examinees into score categories. This article expands on that exposition by evaluating the index as it is likely to be used in practice (as a point estimate of classification accuracy), provides a…

Purpose: This study tested the accuracy with which the MacArthur-Bates Communicative Development Inventories, Level III (CDI-III), a parent report measure of language ability, discriminated children with language impairment from those developing language typically. Method: Parents of 58 children, 49 with typically developing language (age 30 to 42…

Cut scores, quartile ranking, sample size, and overall classification scheme were studied as personnel selection procedures in two samples. The first was 120 simulated observations of employee scores based on actual selection procedures for applicants for administrative assistant positions. The other sample was composed of test results for 73…

Purpose: The normative group of a norm-referenced test is intended to provide a basis for interpreting test scores. However, the composition of the normative group may facilitate or impede different types of diagnostic interpretations. This article considers who should be included in a normative sample and how this decision must be made relative…