A link to the complete Volume 1 is now available. View journal article

The Loyola Experience (1993-2009): Optimal Data Analysis in the Department of Psychology Fred B. Bryant, Ph.D. Loyola University Chicago This article traces the origins and development of the use of optimal data analysis (ODA) within the Department of Psychology at Loyola University Chicago over the past 17 years. An initial set of ODA-based articles by … Continue reading The Loyola Experience (1993-2009): Optimal Data Analysis in the Department of Psychology

Optimal Data Analysis: A General Statistical Analysis Paradigm Paul R. Yarnold, Ph.D., and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC Optimal discriminant analysis (ODA) is a new paradigm in the general statistical analysis of data, which explicitly maximizes the accuracy achieved by a model for every statistical analysis, in the context of exact distribution … Continue reading Optimal Data Analysis: A General Statistical Analysis Paradigm

Maximizing Accuracy of Classification Trees by Optimal Pruning Paul R. Yarnold, Ph.D., and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC We describe a pruning methodology which maximizes effect strength for sensitivity of classification tree models. After deconstructing the initial “Bonferroni-pruned” model into all possible nested sub-branches, the sub-branch which explicitly maximizes mean sensitivity is … Continue reading Maximizing Accuracy of Classification Trees by Optimal Pruning

Two-Group MultiODA: A Mixed-Integer Linear Programming Solution with Bounded M Robert C. Soltysik, M.S., and Paul R. Yarnold, Ph.D. Optimal Data Analysis, LLC Prior mixed-integer linear programming procedures for obtaining two-group multivariable optimal discriminant analysis (MultiODA) models require estimation of the value of a parameter, M. A new formulation is presented which establishes a lower … Continue reading Two-Group MultiODA: A Mixed-Integer Linear Programming Solution with Bounded M

Unconstrained Covariate Adjustment in CTA  Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC In traditional statistical covariate analysis it is common practice to force entry of the covariate into the model first, to eliminate the effect of the covariate (i.e., “equate the groups”) on the dependent measure. In contrast, in … Continue reading Unconstrained Covariate Adjustment in CTA

Maximizing the Accuracy of Probit Models via UniODA  Barbara M. Yarnold, J.D., Ph.D. and Paul R. Yarnold, Ph.D. Optimal Data Analysis, LLC Paralleling the procedure used to maximize ESS of linear models derived using logistic regression analysis or Fisher’s discriminant analysis, univariate optimal discriminant analysis (UniODA) is applied to the predicted response function values provided … Continue reading Maximizing the Accuracy of Probit Models via UniODA

Precision and Convergence of Monte Carlo Estimation of Two-Category UniODA Two-Tailed p Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC Monte Carlo (MC) research was used to study precision and convergence properties of MC methodology used to assess Type I error in exploratory (post hoc, or two-tailed) UniODA involving two … Continue reading Precision and Convergence of Monte Carlo Estimation of Two-Category UniODA Two-Tailed p

Aggregated vs. Referenced Categorical Attributes in UniODA and CTA  Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC Multivariable linear methods such as logistic regression analysis, discriminant analysis, or multiple regression analysis, for example, directly incorporate binary categorical attributes into their solution. However, for categorical attributes having more than two levels, … Continue reading Aggregated vs. Referenced Categorical Attributes in UniODA and CTA

Manual vs. Automated CTA: Optimal Preadmission Staging for Inpatient Mortality from Pneumocystis cariini Pneumonia Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC Two severity-of-illness models used for staging risk of in-hospital mortality from AIDS-related Pneumocystis cariini pneumonia (PCP) were developed using hierarchically optimal classification tree analysis (CTA), with models derived … Continue reading Manual vs. Automated CTA: Optimal Preadmission Staging for Inpatient Mortality from Pneumocystis cariini Pneumonia

Manual vs. Automated CTA: Psychosocial Adaptation in Young Adolescents Rachael Millstein Coakley, Ph.D., Grayson N. Holmbeck,Ph.D., Fred B. Bryant, Ph.D., and Paul R. Yarnold, Ph.D. Children's Hospital, Boston / Harvard Medical School, Loyola University Chicago,  Optimal Data Analysis, LLC Compared to the manually-derived model, the enumerated CTA model was 20% more parsimonious, 3.6% more accurate and 30% … Continue reading Manual vs. Automated CTA: Psychosocial Adaptation in Young Adolescents

Gen-UniODA vs. Log-Linear Model: Modeling Organizational Discrimination  Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC An application involving a binary class variable (gender), an ordinal attribute (academic rank), and two testing periods (separated by six years) was troublesome for the log-linear model, but was easily analyzed using Gen-UniODA. View journal … Continue reading Gen-UniODA vs. Log-Linear Model: Modeling Organizational Discrimination

UniODA vs. Chi-Square: Ordinal Data Sometimes Feign Categorical Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S. Optimal Data Analysis, LLC Assessed using perhaps the most widely used type of measurement scale in all science, ordinal data are often misidentified as being categorical, and incorrectly analyzed by chi-square analysis. Three examples drawn from the literature … Continue reading UniODA vs. Chi-Square: Ordinal Data Sometimes Feign Categorical

The Use of Unconfounded Climatic Data Improves Atmospheric Prediction   Robert C. Soltysik, M.S., and Paul R. Yarnold, Ph.D. Optimal Data Analysis, LLC This report improves measurement properties of data and analytic methods widely used in meteorological modeling and forecasting. Paradoxical confounding is defined and demonstrated using global temperature land-ocean index data. It is shown … Continue reading The Use of Unconfounded Climatic Data Improves Atmospheric Prediction

Here Today, Gone Tomorrow: Understanding Freshman Attrition Using Person-Environment Fit Theory Jennifer Howard Smith, Ph.D., Fred B. Bryant, Ph.D., David Njus, Ph.D., and Emil J. Posavac, Ph.D. Applied Research Solutions, Inc., Loyola University Chicago, Luther College, Loyola University Chicago (Emeritus) Person-Environment (PE) fit theory was used to explore the relationship between student involvement and freshman retention. Incoming … Continue reading Here Today, Gone Tomorrow: Understanding Freshman Attrition Using Person-Environment Fit Theory

Tracing Prospective Profiles of Juvenile Delinquency and Non-Delinquency: An Optimal Classification Tree Analysis Hideo Suzuki, Ph.D., Fred B. Bryant, Ph.D., and John D. Edwards, Ph.D. This study explored multiple variables that influence the development of juvenile delinquency. Two datasets of the National Youth Survey, a longitudinal study of delinquency and drug use among youths from … Continue reading Tracing Prospective Profiles of Juvenile Delinquency and Non-Delinquency: An Optimal Classification Tree Analysis

Automated CTA Software: Fundamental Concepts and Control Commands Robert C. Soltysik, M.S. and Paul R. Yarnold, Ph.D. Optimal Data Analysis, LLC Fundamental methodological concepts are reviewed, and automated CTA software commands are annotated. View journal article

How to Save the Binary Class Variable and Predicted Probability of Group Membership from Logistic Regression Analysis to an ASCII Space-Delimited File in SPSS 17 For Windows Fred B. Bryant, Ph.D. Loyola University, Chicago This note explains the steps involved and provides the SPSS syntax needed to run two-group logistic regression analysis using SPSS 17 … Continue reading How to Save the Binary Class Variable and Predicted Probability of Group Membership from Logistic Regression Analysis to an ASCII Space-Delimited File in SPSS 17 For Windows

An Internet-Based Intervention for Fibromyalgia Self-Management: Initial Design and Alpha Test William Collinge, Ph.D., Robert C. Soltysik, M.S., and Paul R.Yarnold, Ph.D. Collinge and Associates and Optimal Data Analysis, LLC Self-Monitoring And Review Tool, or SMART, is an interactive, internet-based, self-monitoring and feedback system, which helps people discover and monitor links between their own health-related … Continue reading An Internet-Based Intervention for Fibromyalgia Self-Management: Initial Design and Alpha Test

Junk Science, Test Validity, and the Uniform Guidelines for Personnel Selection Procedures: The Case of Melendez v. Illinois Bell Fred B. Bryant, Ph.D. and Elaine K.B. Siegel Loyola University Chicago and Hager & Siegel, P.C. This paper stems from a recent federal court case in which a standardized test of cognitive ability developed by AT&T, … Continue reading Junk Science, Test Validity, and the Uniform Guidelines for Personnel Selection Procedures: The Case of Melendez v. Illinois Bell