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,…

The charter school movement in the United States began in Minnesota in 1991 and spread rapidly in nearly every state within the United States in an attempt to provide competition for the traditional public schools. Since the passage of the first charter school laws, and the most recent legislative passage in Alabama, forty-two state legislatures…

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…

In this study, the perceptions of parents (n = 14) and students (n = 47) enrolled in a blended learning course, the first of its kind at their school, were examined. Student performance in the blended and in the traditional portion of the course was examined, and the Educational Success Prediction Instrument (ESPRI) was administered to predict…

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…

Differential item functioning (DIF) continues to receive attention both in applied and methodological studies. Because DIF can be an indicator of irrelevant variance that can influence test scores, continuing to evaluate and improve the accuracy of detection methods is an essential step in gathering score validity evidence. Methods for detecting…

This study compares the classification accuracy of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR), and classification and regression trees (CART) under a variety of data conditions. Past research has generally found comparable performance of LDA and LR, with relatively less research on QDA and…

Propensity score analysis is one statistical technique that can be applied to observational data to mimic randomization and thus can be used to estimate causal effects in studies in which the researchers have not applied randomization. In this article the authors (a) describe propensity score methodology and (b) demonstrate its application using…

The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…

Methods of adjusting cut scores used in placement decisions are examined empirically. Admission and performance variables are used to study alternate methods of adjusting cut scores for placement in standard and accelerated rhetoric courses in a large university setting, with the predicted variable being success or failure as measured by…

Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…

This book in intended to train students in reading a research report critically. It uses actual research articles as examples including both good and flawed studies in each category and provides interpretation and evaluation of the appropriateness of the statistical analyses in each study. Individual chapters usually include two sample studies and…

This paper explores the feasibility of neural computing methods such as artificial neural networks (ANNs) and abductory induction mechanisms (AIM) for use in educational measurement. ANNs and AIMS methods are contrasted with more traditional statistical techniques, such as multiple regression and discriminant function analyses, for making…

The validity of assumptions that portfolios complement other assessment methods and yield more reliable and valid data than do traditional methods was studied. More specifically, focus was on examining whether: achievement level (characterized by scores, ranks, and group membership) varies significantly with differing definitions and usage of…