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Sex and age were considered as forced variables in the final multivariate models.
To further test for collinearity, each of the other variables was dropped from the model and we observed changes in the standard errors for the forced variables.
Variables that were significant at p < 0.10 were then entered as covariates in a forward step-wise general linear regression model that included the forced variables of gender and age.
To determine independent variables associated with outcome, we performed a complete multivariate analysis including prognostic factors associated with P value < 0.10 in bivariate analysis and, if clinically relevant, some forced variables.
Thirteen variables were included in the multivariate regression analyses for the PS pair (Table 3), along with the forced variables- child's sex and exact age.
Fourteen variables were included in the multivariate regression analyses for the PI pair (Table 3), along with the forced variables- child's sex and exact age.
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We used forced variable entry with catchment area, interviewer experience, and individual interviewer as dummy variables comparing to a referent interviewer, selected as the person with the maximum completed assessments (n = 102).
The forcing variables are discharge, river morphology, water temperature, available light and nutrient inputs.
The model depends on seawater temperature and food density, as forcing variables, followed throughout the whole larval development.
Force control for the extra axes is considered, and appropriate transformations from measured actuator positions and forces to position and force variables used for control are given, although solutions are not unique.
Recent field and theoretical studies suggest that mountain catchments respond transiently to high frequency forcing, and so sediment discharge from the catchment is a non-linear function of forcing variables.
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