This commentary to the recent article by Musso et al. (2013) discusses issues related to model fitting, comparison of classification accuracy of generative and discriminative models, and two (or more) cultures of data modeling. We start by questioning the extremely high classification accuracy with an empirical data from a complex domain. There is…

Adelman (2006) observed that a large quantity of research on retention is "institution-specific or use institutional characteristics as independent variables" (p. 81). However, he observed that over 60% of the students he studied attended multiple institutions making the calculation of institutional effects highly problematic. He argued…

The purpose of this paper is to assist researchers, practitioners, and graduate students in identifying and addressing key questions related to the task of choosing among the analytic techniques designed to analyze a dichotomized dependent variable with a set of independent variables. The discussion is limited to (1) the analysis of data by the…

Used a current attrition study to show the usefulness of discriminative analysis and a cross validation technique applied to student nonpersister questionnaire respondents and nonrespondents. Results of the techniques allowed delineation of several areas of sample under-representation and established the instability of the regression weights…

Conventional statistical significance tests do not inform the researcher regarding the likelihood that results will replicate. One strategy for evaluating result replication is to use a "bootstrap" resampling of a study's data so that the stability of results across numerous configurations of the subjects can be explored. This paper…

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…

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…

STATGRAPHICS, a statistical package written for the IBM PC/XT/AT, is reviewed. In addition to superb graphics, STATGRAPHICS is unequalled in time series procedures, quality control, linear programming, and other mathematical procedures. The modules for regression analysis, categorical data analysis, and nonparametric analysis are good, but contain…

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…