It's a wrap! A link to the complete Volume 3 of Optimal Data Analysis is now available. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Kendall's coefficient of concordance W is a non-parametric statistic used to assess agreement in rankings of multiple stimuli made by multiple raters. A normalization of the test statistic for Friedman’s non-parametric alternative to ANOVA with repeated measures, W ranges from 0 (no agreement) to 1 (complete agreement). Problems … Continue reading UniODA vs. Kendall’s Coefficient of Concordance (W): Multiple Rankings of Multiple Movies

Paul R. Yarnold Optimal Data Analysis, LLC Receiver operator characteristic (ROC) analysis is sometimes used to assess the classification accuracy achieved using an ordered attribute to discriminate a dichotomous class variable, and in this context to identify an “optimal” discriminant cutpoint. In ROC analysis the optimal cutpoint corresponds to the threshold value at which distance … Continue reading UniODA vs. ROC Analysis: Computing the “Optimal” Cut-Point

Paul R. Yarnold Optimal Data Analysis, LLC The Bray-Curtis dissimilarity index is widely-used as an index of the magnitude of compositional dissimilarity in the count of different categories between two samples, yet it fails to address the statistical reliability of the dissimilarity, the precise nature of the dissimilarity, and the potential cross-generalizability of the findings. … Continue reading UniODA vs. Bray-Curtis Dissimilarity Index for Count Data

Paul R. Yarnold Optimal Data Analysis, LLC This study assesses agreement between number of lambs born to 227 ewes over two consecutive years. Polychoric correlation could not be validly used to assess agreement because underlying distributional assumptions were violated. Requiring no distributional assumptions, UniODA identified moderate, statistically significant agreement. View journal article

Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC This article describes and illustrates discrete 95% confidence intervals (CIs) which are computed in novometric analysis for both model- and chance-based classification results. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Globally optimal statistical methods eliminate the greatest challenges to the validity and reproducibility of findings in the literature. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Novometric analysis is used to develop a triage algorithm for rapid ordering of chest radiography for community-acquired pneumonia (CAP), for a retrospective Emergency Department-based matched case-control study providing data on attributes assessed for 100 radiographic confirmed cases of both CAP and influenza-like illness (ILI). Results for the least … Continue reading Triage Algorithm for Chest Radiography for Community-Acquired Pneumonia of Emergency Department Patients: Missing Data Cripples Research

Paul R. Yarnold Optimal Data Analysis, LLC Novometric analysis is used to determine aspects of care which induce greatest satisfaction among Emergency Department (ED) patients. Data were obtained from a satisfaction survey with responses obtained using five-point Likert-type scales. The first analysis discriminated 1,045 strongly satisfied and 671 moderately satisfied patients, and the second analysis … Continue reading What Most Satisfies Emergency Department Patients?

Paul R. Yarnold Optimal Data Analysis, LLC In novometric analysis exact 95% confidence intervals (CIs) are computed for overall model performance and for model endpoints. When CIs overlap for two or more endpoints a model is said to be redundant, meaning that the domain of the outcome cannot be distinguished between overlapping endpoints. This research … Continue reading Illustrating How 95% Confidence Intervals Indicate Model Redundancy

Paul R. Yarnold Optimal Data Analysis, LLC Novometric analysis is used to determine aspects of care which induce greatest dissatisfaction among Emergency Department (ED) patients. Data were obtained from a satisfaction survey on which responses were obtained using five-point Likert-type scales. The first analysis discriminated 131 strongly dissatisfied and 114 moderately dissatisfied patients, and the … Continue reading What Most Dissatisfies Emergency Department Patients?

Paul R. Yarnold Optimal Data Analysis, LLC Novometric analysis is used to discriminate 239 ambivalent versus 584 discharged patients who are likely to recommend the Emergency Department (ED) to others. Findings reveal the critical factors are physician explanation of tests and treatment, and attention paid to the patient by the nurse. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Recent research reported that an Emergency Department (ED) patient’s ratings of how well the physician explained one’s illness or injury is the best discriminator of extreme satisfaction versus extreme dissatisfaction ratings regarding care received in the ED. The present study uses novometric analysis to discriminate 1,012 ED patients … Continue reading What Influences Patients to Recommend an Emergency Department to Others?

Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC Novometrics—meaning new (Latin: novo) measurement, connotes a newly discovered theoretically-motivated algorithm that explicitly identifies the globally-optimal (GO) statistical model underlying any random statistical sample, indicated as S. Originating from the field of operations research, “optimal” denotes explicitly maximized (weighted) classification accuracy for S: that … Continue reading Globally Optimal Statistical Models, II: Unrestricted Class Variable, Two or More Attributes

Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC Imagine a random sample S consisting of a class variable (“dependent measure”), one or more attrib­utes (“independent measures”), a weight (unit-weighted obser­vations are equally-valued), and a number of observations N yielding at least minimally ade­quate statistical power for testing the a priori or post … Continue reading Globally Optimal Statistical Classification Models, I: Binary Class Variable, One Ordered Attribute

Paul R. Yarnold Optimal Data Analysis, LLC An exact, optimal (“maximum-accuracy”) psychometric methodology for assessing inter-method reliability for measures involving ordinal ratings is used to evaluate and compare two emergency medicine triage algorithms—both of which classify patients into one of five ordinal categories. Ten raters independently evaluated the identical set of 200 patients, five with … Continue reading How to Assess the Inter-Method (Parallel-Forms) Reliability of Ratings Made on Ordinal Scales: Emergency Severity Index (Version 3) and Canadian Triage Acuity Scale

Paul R. Yarnold Optimal Data Analysis, LLC An exact, optimal (“maximum-accuracy”) psychometric methodology for assessing inter-observer reliability for measures involving ordinal ratings is used to evaluate and compare two emergency medicine triage algorithms—both of which classify patients into one of five ordinal categories. Ten raters independently evaluated the identical set of 200 patients, five with … Continue reading How to Assess Inter-Observer Reliability of Ratings Made on Ordinal Scales: Evaluating and Comparing the Emergency Severity Index (Version 3) and Canadian Triage Acuity Scale

Fred B. Bryant & Paul R. Yarnold Optimal Data Analysis, LLC Prior research investigating savoring behaviors and Type A behavior (TAB) found that extreme Type A undergraduates are most likely to score in the highest quintile on self-congratulation, and in the lowest three quintiles on memory-building. This study used scores on past-, present-, and future-focused … Continue reading Finding Joy in the Past, Present, and Future: The Relationship Between Type A Behavior and Savoring Beliefs Among College Undergraduates

Fred B. Bryant & Paul R. Yarnold Optimal Data Analysis, LLC This study used scores on measures of dispositional optimism and pessimism to discriminate 117 extreme Type A versus 131 extreme Type B college undergraduates. Consistent with a priori hypotheses the analysis revealed that Type As were significantly less pessimistic, and significantly more optimistic, than … Continue reading Type A Behavior, Pessimism and Optimism Among College Undergraduates

Paul R. Yarnold Optimal Data Analysis, LLC The authors of Chapter 4 complain that use of the word “optimal” in the name Optimal Data Analysis (ODA) is unethical because it implies that alternative data analysis methods are less than optimal. The present Errata note addresses this misunderstanding. View journal article