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Our second goal was to investigate predictors of the slopes for each of HbA1c and BGMF using a bivariate, bidirectional regression model.
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The results for the bidirectional regression model are reported in Table 2.
However, two criticisms may be made of the two-dimensional decomposition analysis based on the bivariate multiple regression model.
The most salient of these decompositions is based on the bivariate multiple regression model that explains both variables simultaneously.
This shows that, using a SEM regression approach, we end up with decomposition (III) based on the bivariate multiple regression model.
The multivariate model was built after fitting the bivariate logistic regression model for all explanatory variables.
We used a separate bivariate logistic regression model for newly diagnosed asthma.
The variables associated with IMT in the bivariate gamma regression model are listed in Table 3.
The bivariate logistic regression model, utilizing the Chi-square test, identified a significant effect of KPC on mortality (p = 0.050).
We calculated odds ratios using a bivariate logistic regression model to explore the strength of the relationship.
For discriminatory power, the two EQ-5D-5L indices were simultaneously regressed on a health indicator in a bivariate regression model.
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