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We repeated each of the above logistic models using multiple regression, with the continuous cognitive measure being regressed on each renal measure and the covariates.
For this, we used multiple regression with regularization parameters.
These results were significant in multiple regression with control variables, at a probability value of.067.
A multiple regression with 'task difficulty' as a regressor ('difficult', 'moderate'easyashowedhowedynamicichangeses in neural activity.
Data for both groups were separately analyzed using multiple regression with 3.5% fat-corrected milk as the dependent variable and BW and DMI as independent variables.
Table 2 shows the results of multiple regression with the undergraduate participants' first semester GPAs as the dependent variable.
Log-transformed CORT/CRP values were analyzed using multiple regression with Holms' adjusted p-values and age, body mass index (BMI), and race as covariates.
Multiple regression with profitability as dependent variable is conducted with the four outsourcing strategies as explanatory variables while simultaneously controlling for enterprise size and strategic direction.
None of the language proficiency indicators entered into the regression via Step 2. The results of graduate participants' multiple regression with first semester GPAs as the dependent variable are shown in Table 4.
In this analysis we performed a multiple regression with the hatching success in controls.
Statistical parametric maps were calculated using multiple regression with the hemodynamic response function modeled in SPM5.
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