Reverse CTA vs. Five-Factor Factorial ANOVA: Purifying a Crystalline Product

Paul R. Yarnold

Optimal Data Analysis, LLC

A five-factor factorial experiment was conducted to assess aspects of the manufacturing process that affected product quality. All factors were binary, and each of the 32 cells in the design had N = 1. The findings of analyses using factorial ANOVA versus using reverse CTA to identify factors influencing quality are contrasted.

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UniODA-Based Structural Decomposition vs. Log-Linear Model: Statics and Dynamics of Intergenerational Class Mobility

Paul R. Yarnold

Optimal Data Analysis, LLC

Analysis assessed structure underlying the cross-classification of social class of N = 9,434 son’s aged 20-64 years, and their father’s social class when the son was 14 years of age. No satisfactory log-linear model was identified. UniODA-based structural decomposition analysis identified four models that together yielded a strong effect.

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Predicting Divorce: The Role of Gender, and of Pre- and Extra-Marital Sex

Paul R. Yarnold

Optimal Data Analysis, LLC

A survey-based study comparing N = 494 divorcees and N = 542 married people collected binary data for three attributes: respondent gender; if the respondent reported having pre-marital sex (PMS); and if the respondent reported having extra-marital sex (EMS). Analysis via globally-optimal CTA (GO-CTA) identified a moderately strong (ESS = 26.3) model that employed both sexual behavior attributes to correctly classify 83.4% of married and 42.9% of divorced people.

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