Paul R. Yarnold Optimal Data Analysis, LLC This note identifies psychometric research using ODA to assess inter-rater, inter-method and test-retest reliability of scores made using the Naranjo Adverse Drug Reaction Probability (APS) Scale. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC This note compiles initial research exploring the use of ODA in Markov process modelling. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC This note illustrates visualizing an ODA optimal cutpoint used to classify observations in training or validity samples, and summarizing resulting accuracy using the confusion matrix and PAC, ESS and D indexes. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Satisfaction ratings (1=very dissatisfied; 2=somewhat dissatisfied; 3=neutral; 4=somewhat satisfied; 5=very satisfied) provided by 4,583 hospital patients in three successive cohorts (two consecutive 3-month-long base¬line cohorts and one 3-month-long post-intervention cohort) were compared to evaluate a program which was designed to increase patient-rated satisfaction with in-hospital received care (Table … Continue reading Comparing Exact Discrete 95% CIs for Model vs. Chance ESS to Evaluate Statistical Significance

Paul R. Yarnold Optimal Data Analysis, LLC Cross-classification tables may be created for one or more “cohorts”— groups of observations defined by a common event such as the year of one’s birth, graduation, employment, marriage, disease diagnosis or incarceration—and assessed at two or more points in time on one or more variables reflecting the substantive … Continue reading Optimal Analyses for Cohort Tables

Paul R. Yarnold Optimal Data Analysis, LLC When a first-order Markov model cannot be confirmed one approach is subdividing the sample into strata each having a distinct set of transition probabilities. This note demonstrates the use of ODA to assess whether stratification resulted in significantly different transition matrices. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC This note demonstrates the use of ODA to test the hypothesis of an underlying second-order Markovian process. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Sufficiently iterated over time periods a first order Markovian change process defined by a constant transition matrix yields a steady state. Consecutive transition matrices are compared by Goodman’s chi-square test to assess if a steady state has been achieved. This note demonstrates the analogous use of ODA to … Continue reading Using ODA to Confirm a First Order Markov Steady State Process

Ariel Linden & Paul R. Yarnold Linden Consulting Group, LLC & Optimal Data Analysis, LLC Diagnostic screening tests are used to predict an individual’s graduated disease status which is measured on an ordered scale assessing disease progression (severity of illness). Maximizing the predictive accuracy of the diagnostic or screening test is paramount to correctly identifying … Continue reading Comparative Accuracy of a Diagnostic Index Modeled Using (Optimized) Regression vs. Novometrics

Ariel Linden & Paul R. Yarnold Linden Consulting Group, LLC & Optimal Data Analysis, LLC Maximizing the discriminatory accuracy of a diagnostic or screening test is paramount to correctly identifying individuals with vs. without the disease or disease marker. In this paper we demonstrate the use of ODA to identify the optimal cut-point which best … Continue reading Identifying Maximum-Accuracy Cut-Points for Diagnostic Indexes via ODA

Ariel Linden & Paul R. Yarnold Linden Consulting Group, LLC & Optimal Data Analysis, LLC Data from the National Supported Work (NSW) randomized experiment have been used frequently over the past 30 years to demonstrate the implementation of various non-experimental methods for drawing causal inferences about treatment effects. In the present study we reanalyze the … Continue reading Reanalysis of the National Supported Work Experiment Using ODA

Ariel Linden & Paul R. Yarnold Linden Consulting Group, LLC & Optimal Data Analysis, LLC In a recent series of papers, ODA has been applied to observational data to draw causal inferences about treatment effects. Presently, ODA is applied to survival outcomes from a randomized controlled trial, with a reanalysis of a study by Linden … Continue reading Using ODA in the Evaluation of Randomized Controlled Trials: Application to Survival Outcomes

Ariel Linden & Paul R. Yarnold Linden Consulting Group, LLC & Optimal Data Analysis, LLC In a recent series of papers, ODA has been applied to observational data to draw causal inferences about treatment effects. In this article ODA is applied to data from a randomized controlled trial, with a reanalysis of a study by … Continue reading Using ODA in the Evaluation of Randomized Controlled Trials

Paul R. Yarnold Optimal Data Analysis, LLC Two prediction-interval scaling strategies are illustrated for a 10-point ordinal attribute: one strategy compresses the most extreme scores, and the other strategy compresses the least extreme scores on the scale. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC This first correspondence note addresses the question of how one may obtain a personal copy of ODA, MegaODA and/or CTA software. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC For class variables with two categories, ODA and MegaODA software employ Fisher’s one-tailed exact test to assess p associated with LOO classification performance. For class variables having three or more categories, LOO p is not provided. This article discusses how to use ODA and MegaODA software to obtain … Continue reading Obtaining LOO p in Analysis Involving Three or More Class Categories

Paul R. Yarnold Optimal Data Analysis, LLC ANOVA with three between-groups factors is used to compare an ordered attribute (score) between four independent categories of class variable “A”, three independent categories of class variable “B”, and two independent categories of class variable “C”. The novometric multiple regression analogue is demonstrated. View journal article

Ariel Linden & Paul R. Yarnold Linden Consulting Group, LLC & Optimal Data Analysis, LLC In 1997, Australia implemented a gun buyback program that reduced the stock of firearms by around one-fifth, and nearly halved the number of gun-owning households. Leigh and Neill evaluated if the reduction in firearms availability affected homicide and suicide rates, … Continue reading The Australian Gun Buyback Program and Rate of Suicide by Firearm

Paul R. Yarnold Optimal Data Analysis, LLC ANOVA with two between-groups factors is used to compare an ordered attribute (score) between four independent categories of class variable “A”, and three independent categories of class variable “B”. The novometric multiple regression analogue is demonstrated. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC An integer attribute (dependent) variable is compared between four categories of a class (independent) variable using ANOVA with one between-groups factor, as well as novometric analogues to ANOVA (to predict class status) and to multiple regression (to predict score). View journal article