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Next, we introduce the regression model for diversification in Sect.

Section 3 introduces the regression model and prior distribution used to infer the model parameters representing gene gene influences.

This measure was introduced in regression models with adjustment for the overall proportion of migrants.

As such, the interaction term for intervention × diabetes, intervention × CVD, and diabetes × CVD were introduced into regression models.

In the subsequent section, we introduce the regression models used to study the effects of participant characteristics on the number of contacts people make.

The two scales measuring supply chain uncertainty correlated at 42% indicating potential for collinearity if they are both introduced in the regression model.

Although univariate analysis showed that children from better-off households were 2-times more likely to access the ACT promptly than the poor this effect was diluted when other variables were introduced in the regression model.

Third, to simplify computations for some data sets, we introduced a logistic regression model.

The rating on the 3-point scales was introduced in the regression model as an interval scale since the variables had a linear approximation with our dependent variable.

As visual acuity was the dominate factor in determining the quality of life, the visual status was also introduced into the regression model as a variable.

All other variables associated with serum biomarkers in univariate analysis at p < 0.10 were introduced into the regression model as independent variables.