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Then, to identify the predictors of sexual behaviors among ART attendants, only variables that were significantly associated in the bivariate analysis were entered into multinomial regression modes.
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Multinomial regression analysis stratified by type of labour onset examined the association between pre-pregnancy BMI and mode of delivery controlling for maternal age, pre-existent health conditions, parity, fertility treatments, history of C-section and pregnancy complications.
Deep Dirichlet Multinomial Regression.
Implementation of Deep Dirichlet Multinomial Regression in python + cython.
Group-based trajectory modeling identified QOL trajectories; multinomial regression evaluated effects of predictors on trajectory groups.
Finally, a multinomial regression analysis was used to predict ECEC usage before school entry.
Typological variables with no natural ordering were predicted using multinomial regression (proportional odds logistic regression).
Logistic regression is a multinomial regression model and it is used for prediction by fitting data to a logistic curve.
Logistic regression or multinomial regression was performed.
This was examined through multinomial regression analysis.
Logistic regression and multinomial regression was the performed analyzes.
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