Paul R. Yarnold Optimal Data Analysis, LLC The effectiveness of a new flu vaccine requiring two administrations spaced by two weeks was incorrectly evaluated using chi-square analysis: findings are compared between chi-square and UniODA. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Whereas omnibus effects identified using chi-square to assess association in R x C contingency tables are often difficult or impossible to disentangle when R and C are greater than two, identifying the structure underlying R x C tables using UniODA is straightforward. An investigation of the association between … Continue reading UniODA vs. Chi-Square: Deciphering R x C Contingency Tables

Paul R. Yarnold Optimal Data Analysis, LLC The Adverse Drug Reaction Probability Scale (APS) is an algorithm that is used to rate the probability that an adverse drug event is drug-induced. Prior research compared the reliability of APS ratings generated by 15 pairs of independent experts between baseline and training, versus between training and three-month … Continue reading UniODA vs. Eyeball Analysis: Comparing Repeated Ordinal Scores

Paul R. Yarnold Optimal Data Analysis, LLC The Adverse Drug Reaction Probability Scale (APS) is used to rate the probability that an adverse drug event is drug-induced. Prior research compared the inter-rater reliability of APS ratings generated by 15 pairs of independent experts at two testings: (1) immediately after training, and (2) three months after … Continue reading UniODA vs. Sign Test: Comparing Repeated Ordinal Scores

Paul R. Yarnold Optimal Data Analysis, LLC The Adverse Drug Reaction Probability Scale (APS) algorithm is widely-used for rating the probability that an adverse drug event is drug-induced. Prior research (Figure 1, p. 695) presented APS ratings generated by two independent experts for N = 129 challenging cases. Between-rater reliability of these ratings is computed … Continue reading UniODA vs. Spearman Rank ρ: Between-Raters Reliability of Scores on the Adverse Drug Reaction Probability Scale

Paul R. Yarnold Optimal Data Analysis, LLC Prior research employed t-test to compare mean uptake of [11C]5-HTP across the blood-brain barrier for eight healthy volunteers versus six patients with unipolar depression, however no statistically significant mean difference was identified for basil ganglia, caudate nucleus, or lentiform nucleus. When analyzed via UniODA, significantly lower mean uptake … Continue reading UniODA vs. t-Test: Low Brain Uptake of L-[11C]5-hydroxytryptophan in Major Depression

Paul R. Yarnold Optimal Data Analysis, LLC UniODA-based classification models involving one attribute yielded greater overall, maximum, and minimum classification accuracy in modeling 10-year population change than legacy models involving five attributes and derived using either logistic regression analysis or Fisher’s linear discriminant analysis. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC A maximum-corrected measure of effect size for chi-square is compared with an alternative measure that is maximum- and chance-corrected, for an application assessing the relationship between voting on the Refugee Act of 1980 and political affiliation in the U.S. House of Representatives. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Maximum-corrected and chance-corrected measures of effect size for the Q test are compared. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Gender and psychology concentration are cross-classified for N = 100 graduate students, resulting in a 2 x 5 contingency table. Estimating the nature and magnitude of the association between these variables by legacy statistical methods is inappropriate owing to computational and interpretative difficulties. However, obtaining and interpreting the … Continue reading Gender and Psychology Concentration for Graduate Students

Paul R. Yarnold Optimal Data Analysis, LLC To assess if going first is an advantage in the card-game cribbage, an experienced human cribbage player competed against a computer for 100 games. When findings were analyzed using non-directional chi-square analysis there was no statistically significant effect. However, analysis using confirmatory UniODA revealed that the first move … Continue reading Is Going First an Advantage in Cribbage?

Paul R. Yarnold Optimal Data Analysis, LLC An intuitive example of a nonlinear UniODA model is presented. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC The Kruskal-Wallace test and UniODA are both used to compare investigator-ranked dominance ratings of male versus female dogs. Exposition highlights the insufficiency of statistical reliability as a singular criterion for evaluating model performance, as well as the importance of testing confirmatory hypotheses in the context of increasing statistical … Continue reading UniODA vs. Kruskal-Wallace Test: Gender and Dominance of Free-Ranging Domestic Dogs in the Outskirts of Rome

Paul R. Yarnold Optimal Data Analysis, LLC Cochran’s Q test and UniODA are used to evaluate the reptile display behavior of a dozen pet stores across four major US holiday seasons. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC The use of Cochran’s Q test and UniODA to evaluate success rate is compared for a web usability testing application with four participants performance-assessed on six tasks. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Cochran’s Q test and UniODA are compared in an application comparing the success of alternative tasks. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Kruskal-Wallace test and UniODA are compared in an application comparing corn yield produced by four different farming methods. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC This paper demonstrates a maximum-accuracy statistical approach that assesses the effect of two or more confounding variables on the estimated association of a class variable and attribute(s). An example involves modeling patient self-ratings of the likelihood that they will recommend an Emergency Department to others (class variable), based … Continue reading Optimal Statistical Analysis Involving Multiple Confounding Variables

Paul R. Yarnold Optimal Data Analysis, LLC Statistical evaluation of a treatment effect in the context of a known confounder is contrasted between globally-optimal classification tree analysis (GO-CTA) and marginal structural model (MSM) methods. Unlike MSM, the validity of GO-CTA doesn’t require data to satisfy numerous assumptions, and maximum-accuracy models explicitly identify underlying structure and … Continue reading GO-CTA vs. Marginal Structural Model: Observed Data from a Point-Treatment Study, Stratified by Known Confounder

Paul R. Yarnold Optimal Data Analysis, LLC This paper compares maximum-accuracy statistical approaches that address the effect of a confounding variable on estimated association of class variable and attribute. An example involves modeling patient ratings of likelihood they will recommend an Emergency Department to others (class variable) on the basis of five aspects of physician … Continue reading Optimal Statistical Analysis Involving a Confounding Variable