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We used co-morbidity data from the questionnaire for multivariate and multivariable analyses.
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Bivariate and multivariate analyses were conducted and multivariable associations were reported using odds ratios and 95% confidence intervals.
Two multivariate multivariable statistical models were created: The UMod included males and females without variables related to oestrous cycle, while the FMod included only females with all analysed variables.
PSE solutions appropriate for these challenges involve harnessing multivariate statistics, automated modeling approaches like genetic programming, and multivariable model-based control.
Extension to state variable systems and multivariable control with observers.
Uses the language of vectors and multivariable calculus.
Prerequisites: some familiarity with probability, programming, and multivariable calculus.
Univariable and multivariable logistic regression was used to analyze reinduction failure rates at the first and later salvage attempts.
Statistical Analysis: Both descriptive and multivariable logistic regression analyses.
Bivariate and multivariable prognostic factor/outcome associations were extracted.
The same was true for unpaired and multivariable analyses.
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