Paul R. Yarnold Optimal Data Analysis, LLC The effect of serum cholesterol level on coronary heart disease and mortality was assessed for middle aged diabetic men in a prospective population study.1 Logistic regression was used to test the linear trend over quintiles, yielding estimated p<0.02. However the validity of the estimated Type I error rate … Continue reading UniODA vs. Logistic Regression: Serum Cholesterol and Coronary Heart Disease and Mortality Among Middle Aged Diabetic Men

Paul R. Yarnold Optimal Data Analysis, LLC This 27-year follow-up investigated long-term stability of Type A behavior (TAB) for 1,180 surviving participants in the Western Collaborative Group Study. The kappa statistic was used to assess reliability among and between self- and Structured Interview-based TAB assessments. Results indicated fair temporal reliability for self-assessments (kappa=0.39), moderate temporal … Continue reading UniODA vs. Kappa: Evaluating the Long-Term (27-Year) Test-Retest Reliability of the Type A Behavior Pattern

Paul R. Yarnold Optimal Data Analysis, LLC This study investigated the concordance between clinician and patient assessments of patient’s physical and mental functioning, made using 4-category ordinal scales, for a consecutive sample of 166 outpatients with rheumatoid arthritis. Weighted kappa isn’t a normed statistic, but the respective weighted kappa statistic obtained for the assessments, 0.39 … Continue reading UniODA vs. Weighted Kappa: Evaluating Concordance of Clinician and Patient Ratings of the Patient’s Physical and Mental Health Functioning

Paul R. Yarnold Optimal Data Analysis, LLC Kagan and Snidman investigated processes mediating early reactivity to stimulation in a longitudinal study of 94 four-month-old infants who displayed a combination of either high motor activity and frequent crying, or low motor activity and infrequent crying. Fearful behavior assessed at 9 and 14 months of age was … Continue reading UniODA vs. Chi-Square: Discriminating Inhibited and Uninhibited Infant Profiles

Paul R. Yarnold Optimal Data Analysis, LLC This study evaluates the number of migraine attacks experienced in a clinical trial of two alternative treatments, for a sample of 67 patients. Several conventional statistical methods were used to compare the number of attacks between treatments, but all of these methods were compromised by violations of their … Continue reading UniODA vs. Student’s t-Test: Comparing Two Migraine Treatments

Paul R. Yarnold Optimal Data Analysis, LLC This study compares 10-month-old infant smile status and inter-glance interval for attentive versus inattentive mothers. Statistical analysis by chi-square found no significant effects, while UniODA found that infants with inattentive mothers smile less often, with greater inter-glance intervals. View journal article

It's a wrap! A link to the complete Volume 2 is now available. View journal article

A link to the complete Volume 1 is now available. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC Qualitative data analysis is a structured observational and clustering methodology which facilitates hypothesis development and variable generation for quantitative research, fruitfully employed in agriculture, anthropology, astronomy, biology, forensic investigation, education, history, marketing, medicine, political science, psychology, sociology, and zoology, to name a handful of diciplines. The method known … Continue reading Statistical Evaluation of the Findings of Qualitative Comparative Analysis

Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC Confirmatory hypothesis-testing methodology was recently demonstrated with an example assessing the effect of airborne beta nuclear radiation emanating from the Fukushima nuclear meltdown on the risk of confirmed congenital hypothyroidism (CH) for newborns in California in the years 2011-2012. Eyeball inspection of the data … Continue reading Exploratory Analysis for an Ordered Series of a Dichotomous Attribute: Airborne Radiation and Congenital Hypothyroidism of California Newborns

Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC Ordered series involving a dichotomous (binary) variable are widely used to describe changes in phenomena which occur across time. Examples of such series include the percentage of a sample or population each year (or other unit of time) that marries, dies, or is arrested. … Continue reading Confirmatory Analysis for an Ordered Series of a Dichotomous Attribute: Airborne Radiation and Congenital Hypothyroidism of California Newborns

Paul R. Yarnold & Robert C. Soltysik Optimal Data Analysis, LLC This third time trial of newly-released MegaODA™ software studies the fastest-to-analyze application, known as a 2x2 cross-classification table. Designs involving unweighted binary data are arguably currently the most widely employed across quantitative scientific disciplines as well as engineering fields including communications, graphics, data compression, … Continue reading MegaODA Large Sample and BIG DATA Time Trials: Maximum Velocity Analysis

Paul R. Yarnold Optimal Data Analysis, LLC Recent research tested the hypothesis that the annual crude mortality rate (ACMR) was higher after versus before 1998 in counties of North Dakota, due to increased exposure of the population to environmental toxins and hazards beginning approximately at that time. This hypothesis was confirmed with experimentwise p<0.05 for … Continue reading Determining When Annual Crude Mortality Rate Most Recently Began Increasing in North Dakota Counties, I: Backward-Stepping Little Jiffy

Paul R. Yarnold Optimal Data Analysis, LLC Published monthly by the Survey Research Center of the University of Michigan, the Index of Consumer Sentiment (ICS) is widely followed, and one of its factors (the Index of Consumer Expectations) is used in the Leading Indicator Composite Index published by the US Department of Commerce, Bureau of … Continue reading Surfing the Index of Consumer Sentiment: Identifying Statistically Significant Monthly and Yearly Changes

Paul R. Yarnold Optimal Data Analysis, LLC Mean scores on a continuous dependent measure are compared across three or more groups using one-way analysis of variance (ANOVA). If a statistically significant overall or “omnibus” effect emerges, then a multiple comparisons procedure is used to ascertain the exact nature of any interclass differences. In contrast, the … Continue reading ODA Range Test vs. One-Way Analysis of Variance: Patient Race and Lab Results

Robert C. Soltysik & Paul R. Yarnold Optimal Data Analysis, LLC In research involving multiple tests of statistical hypotheses the efficiency of Monte Carlo (MC) simulation used to estimate the Type I error rate (p) is maximized using a two-step procedure. The first step is identifying the effects that are not statistically significant or ns. … Continue reading MegaODA Large Sample and BIG DATA Time Trials: Harvesting the Wheat

Paul R. Yarnold & Gordon C. Brofft Optimal Data Analysis, LLC Among the most popular conventional statistical methods, Student’s t-test is used to compare the means of two groups on a single dependent measure assessed on a continuous scale. When three or more groups are compared, t-test is generalized to one-way analysis of variance (ANOVA). … Continue reading ODA Range Test vs. One-Way Analysis of Variance: Comparing Strength of Alternative Line Connections

Robert C. Soltysik & Paul R. Yarnold Optimal Data Analysis, LLC Just-released MegaODA™ software is capable of conducting UniODA analysis for an unlimited number of attributes using samples as large as one million observations. To minimize the computational burden associated with Monte Carlo simulation used to estimate the Type I error rate (p), the first … Continue reading MegaODA Large Sample and BIG DATA Time Trials: Separating the Chaff

Paul R. Yarnold Optimal Data Analysis, LLC This note presents SAS™ code for creating a requisite data set and UniODA™ and MegaODA™ code for maximizing the accuracy (ESS) of a multiple regression analysis-based model involving a Likert-type dependent measure with ten or fewer response options. View journal article

Paul R. Yarnold Optimal Data Analysis, LLC A scant few weeks ago disentanglement of effects identified in purely categorical designs in which all variables are categorical, including notoriously-complex rectangular categorical designs (RCDs) in which variables have a different number of response categories, was poorly understood. However, univariate and multivariate optimal (“maximum-accuracy”) statistical methods, specifically UniODA … Continue reading Univariate and Multivariate Analysis of Categorical Attributes with Many Response Categories