This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…

This study compared reading rate to reading fluency (as measured by a rating scale). After listening to first graders read short passages, we assigned an overall fluency rating (low, average, or high) to each reading. We then used predictive discriminant analyses to determine which of five measures--accuracy, rate (objective); accuracy, phrasing,…

In this paper we consider discrimination-aware classification of educational data. Mining and using rules that distinguish groups of students based on sensitive attributes such as gender and nationality may lead to discrimination. It is desirable to keep the sensitive attributes during the training of a classifier to avoid information loss but…

The authors examined the distributional properties of 3 improvement-over-chance, I, effect sizes each derived from linear and quadratic predictive discriminant analysis and from logistic regression analysis for the 2-group univariate classification. These 3 classification methods (3 levels) were studied under varying levels of data conditions,…

In the formation education that is carried out within the scope of undergraduate and non-thesis graduate programs within the same university, different criteria are used to evaluate students' success. In this study, classification accuracy of letter grades that are generated to evaluate students' success using relative and absolute criteria and…

The triad dimensions of complexity, accuracy, and fluency (CAF) has been widely used for assessing second language performance and development. Unlike accuracy and fluency, the construct of Chinese syntactic complexity has not been comprehensibly conceptualized or operationalized. Moreover, not tailored to the typological differences such as the…

The statistical classification of "N" individuals into "G" mutually exclusive groups when the actual group membership is unknown is common in the social and behavioral sciences. The results of such classification methods often have important consequences. Among the most common methods of statistical classification are linear discriminant analysis,…

A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…

A total of 47 gifted and nongifted African American and Euro-American elementary students were rated by their teachers on a multidimensional instrument developed to minimize language considerations and to rely on local norms (Universal Multiple Abilities Scales [UMAS; McCallum & Bracken, 2012a]). Results from two factorial MANOVAs revealed no…

Background: Traditional disability categories may reveal little of the functional characteristics and social competence of a child. Objective: To compare the social competence of typically developing children, children with established disabilities and undiagnosed children identified by a functional approach to be in need of special support.…

A method for comparing the cross-validated classification accuracies of linear and quadratic classification rules is presented under varying data conditions for the "k"-group classification problem. Separate-group and total-group proportions of correct classifications can be compared for the two rules, as is illustrated. (Author/SLD)

A method for comparing the cross-validated classification accuracy of Fisher's linear classification functions (FLCFs) and the least absolute deviation is presented under varying data conditions for the two-group classification problem. With this method, separate-group as well as total-sample proportions of current classifications can be compared…

This study compared the classification performance among parametric discriminant analysis, nonparametric discriminant analysis, and logistic regression in a two-group classification application. Field data from an organizational survey were analyzed and bootstrapped for additional exploration. The data were observed to depart from multivariate…

Multiple samples of university students (N = 1,537) completed the Almost Perfect Scale-Revised (APS-R; R. B. Slaney, M. Mobley, J. Trippi, J. Ashby, & D. G. Johnson, 1996). Cluster analyses, cross-validated discriminant function analyses, and receiver operating characteristic curves for sensitivity and specificity of APS-R scores were used to…

Cross-validated classification accuracies were compared under assumptions of equal and varying degrees of unequal prior probabilities of group membership for 24 bootstrap and 48 simulated data sets. The data sets varied in sample size, number of predictors, relative group size, and degree of group separation. Total-group hit rates were used to…