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
Author: paulyarnold
Increasing the Validity and Reproducibility of Scientific Findings
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
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 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
What Most Satisfies Emergency Department Patients?
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?
Illustrating How 95% Confidence Intervals Indicate Model Redundancy
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
What Most Dissatisfies Emergency Department Patients?
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?
Increasing the Likelihood of an Ambivalent Patient Recommending the Emergency Department to Others
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
What Influences Patients to Recommend an Emergency Department to Others?
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?
Globally Optimal Statistical Models, II: Unrestricted Class Variable, Two or More Attributes
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
Globally Optimal Statistical Classification Models, I: Binary Class Variable, One Ordered Attribute
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
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-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
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
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
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 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
Type A Behavior, Pessimism and Optimism 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
“A Statistical Guide for the Ethically Perplexed” (Chapter 4, Panter & Sterba, Handbook of Ethics in Quantitative Methodology, Routledge, 2011): Clarifying Disorientation Regarding the Etiology and Meaning of the Term Optimal as Used in the Optimal Data Analysis (ODA) Paradigm
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
“Predicting In-Hospital Mortality of Patients with AIDS-Related Pneumocystis carinii Pneumonia: An Example of Hierarchically Optimal Classification Tree Analysis” (Yarnold et al., Statistics in Medicine, 1997, 16, 1451-1463): Corrected Illustration of CTA Model
Paul R. Yarnold Optimal Data Analysis, LLC The lead note in the Errata section of Optimal Data Analysis presents the corrected illustration of the first CTA model published in the field of medicine, two decades ago. View journal article
Type A Behavior and Savoring Among College Undergraduates: Enjoy Achievements Now—Not Later
Fred B. Bryant & Paul R. Yarnold Optimal Data Analysis, LLC Recent research tested the a priori hypothesis that Type A Behavior (TAB) undermines enjoyment of leisure time, and that this effect is mediated by savoring responses which hamper enjoyment. Findings suggested that the hypothesized A-B differences in savoring reflect differences in perfectionism rather than … Continue reading Type A Behavior and Savoring Among College Undergraduates: Enjoy Achievements Now—Not Later
Hierarchically Optimal Classification Tree Analysis of Adverse Drug Reactions Secondary to Warfarin Therapy
Robert C. Soltysik & Paul R. Yarnold Optimal Data Analysis, LLC Identification and detection of adverse drug reactions (ADRs) is critical to patient safety improvement, and warfarin is a medication known to be associated with a high rate of ADRs. Hierarchically optimal CTA was used to predict ADRs attributable to medications taken in addition to … Continue reading Hierarchically Optimal Classification Tree Analysis of Adverse Drug Reactions Secondary to Warfarin Therapy
Emergency Severity Index (Version 3) Score Predicts Hospital Admission
Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC Hospital admission status, Emergency Severity Index (ESI) Version 3 triage score, and binary indicators of whether lab work or radiological examinations were completed in the Emergency Department (ED), were available for 160,471 patients seen over a three-year period in the ED of a leading … Continue reading Emergency Severity Index (Version 3) Score Predicts Hospital Admission
“Breaking-Up” an Ordinal Variable Can Reduce Model Classification Accuracy
Paul R. Yarnold Optimal Data Analysis, LLC Arbitrary parsing of ordinal variables is omnipresent throughout the literature. A hypothetical example demonstrates how arbitrary parsing can reduce the accuracy of a statistical model. View journal article
