Paul R. Yarnold, Ph.D., Nathaniel J. Rhodes, Pharm.D., Ariel Linden, Dr.P.H. Optimal Data Analysis, LLC; Chicago College of Pharmacy, Midwestern University; Linden Consulting Group, LLC Overviews of optimal discriminant analysis (ODA) and novometric theory are presented. Discussion addresses the role of accuracy in translational and precision forecasting research, and of parsimony in theoretical research; the … Continue reading Overview of the Optimal Discriminant Analysis and Novometric Paradigm

Paul R. Yarnold, Ph.D., Fred B. Bryant, Ph.D., Ariel Linden, Dr.P.H. Optimal Data Analysis, LLC, Loyola University Chicago, Linden Consulting Group, LLC We demonstrate the use of optimal data analysis to obtain a hierarchically optimal classification tree-based propensity score model for an application with three (treatment) groups, and to assess outcome differences between treatment groups … Continue reading Using ODA to Estimate Propensity-Weight-Adjusted Treatment Effects for Multi-Valued Treatments

Paul R. Yarnold, Ph.D. and Ariel Linden, Dr.P.H. Optimal Data Analysis, LLC and Linden Consulting Group, LLC This paper illustrates testing directional hypotheses for test-retest Likert ratings of positive and negative emotional states and personality traits for males and females, using the Stata package for implementing ODA. View journal article

Ariel Linden, Dr. P.H. Linden Consulting Group, LLC This paper demonstrates how the random forest algorithm can be used in conjunction with ODA to estimate treatment effects for multivalued treatments using the new Stata package for implementing ODA. View journal article

Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper illustrates testing a directional (i.e., confirmatory) hypotheses for a split-half reliability study using a polychotomous attribute having four categories, via the Stata package for implementing ODA. View journal article

Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper illustrates testing a directional (i.e., confirmatory) hypotheses for a parallel-forms reliability study using a binary and an ordered measure, via the Stata package for implementing ODA. View journal article

Ariel Linden, Dr. P.H. and Paul R. Yarnold, Ph.D. Linden Consulting Group, LLC & Optimal Data Analysis, LLC This paper demonstrates how boosted regression can be used in conjunction with ODA to estimate treatment effects for multivalued treatments using the new Stata package for implementing ODA. View journal article

Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper illustrates testing directional (confirmatory) and non-directional (exploratory) hypotheses for an inter-rater reliability study using a three-category ordinal measure, via the Stata package for implementing ODA. View journal article

Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper describes how to test a non-directional (exploratory) hypothesis for a design relating a three-category class (“dependent”) variable and a continuous attribute vis-à-vis the Stata package for implementing ODA. View journal article

Michael J. Maloney, Nathaniel J. Rhodes & Paul R. Yarnold Proof School, Midwestern University & Optimal Data Analysis LLC SARS-CoV-2 is the beta-coronavirus responsible for COVID-19. Facemask use has been qualitatively associated with reduced COVID-19 cases, but no study has quantitatively assessed the impact of government mask mandates (MM) on new COVID-19 cases across multiple … Continue reading Mask Mandates Can Rapidly and Efficiently Limit COVID-19 Spread: Month-Over-Month Effectiveness of Governmental Policies in Reducing the Number of New COVID-19 Cases in 37 US States and the District of Columbia

Michael J. Maloney Proof School As the number of COVID-19 deaths in the US increased, various policies were enacted in an effort to slow the spread of the pandemic. As sufficient data accumulate over time, the impact of policy on public health outcomes may be statistically evaluated. The present paper uses ODA to evaluate the … Continue reading Mask Mandate Prevented COVID-19 Deaths in Minnesota

To run the MegaODA software within R, download the ODA package for R available at GitHub and created by Dr. Nathaniel J. Rhodes and Dr. Paul Yarnold. This package serves as an interface for the MegaODA software suite. To utilize this package obtain a licensed copy of the MegaODA software. Once MegaODA is obtained and … Continue reading MegaODA software within R: Package now available on GitHub

Paul R. Yarnold, Ph.D. Optimal Data Analysis, LLC Statistically unmotivated exploratory parametric analysis reported that the mean number of monthly consults at an academic otolaryngology service in 2014-2015 was significantly lower than in 2017-2018, suggesting a trend involving increasing numbers of consults over time. Evaluating these data, exploratory novometric temporal analysis identified a globally optimal … Continue reading Novometric Temporal Analysis of Monthly Otolaryngology Service Consults Over Five Consecutive Years

Michael J. Maloney Proof School Users running MegaODA and/or CTA software using the Windows-10 operating system may execute programs more efficiently than vis-à-vis the standard procedure of using the command prompt. View journal article

Ariel Linden Linden Consulting Group, LLC Boosted regression (BR) has been recommended as a machine learning alternative to logistic regression for estimating the propensity score because of its greater accuracy. Commonly known as multiple additive regression trees, BR is a general, automated, data-adaptive modelling algorithm which can estimate the non-linear relationship between treatment assignment (the … Continue reading Comparing CTA to Boosted Regression for Estimating the Propensity Score (Invited)

Paul R. Yarnold Optimal Data Analysis LLC Novometric classification tree analysis was used to evaluate Surveillance, Epidemiology, and End Results (SEER) Program data to discover cancer sites moderately or relatively strongly predicted by male vs. female gender. Future research using any of the 13 cancer sites which met this criterion should account for gender using … Continue reading Differing Cancer-Incidence Rates of Male vs. Female Americans

Paul R. Yarnold Optimal Data Analysis LLC Surveillance, Epidemiology and End Results (SEER) Program data were used to find cancer sites with at least moderately different rates for African vs. Caucasian Americans. Future research in ten cancer sites which involves subjects represented by these groups should account for associated cancer-incidence disparity in matching or via … Continue reading Disparate Cancer-Incidence Rates of Caucasian vs. African Americans

Paul R. Yarnold Optimal Data Analysis LLC This note interprets a novometric descendant family (DF) as an optimal “cluster” analysis indicating number of discriminable groups and strength of their differences at every differentiable point identified for the sample. View journal article