Sentence examples for bivariate linear regression model from inspiring English sources

Potential confounders were identified and included as model covariates if they were significant predictors of the outcome (p < 0.05) in a bivariate linear regression model.

Of the variables studied, only PD ≥4 mm and systolic blood pressure demonstrated a significant association in the bivariate linear regression model (Table  3).

In a bivariate linear regression model (LOS as the dependent variable and ADEs as independent), the slope coefficient was 2.75 (p=0.001), meaning that each ADE corresponded to an increase of 2.75 days in the LOS.

However, when the effect of CNS count was analyzed in a bivariate linear regression model, together with that of CREB, the effect of the CNS was completely (MCAO) or nearly completely (kainate) dependent on the CNSs' content of Creb-binding motifs.

Bivariate linear regression models estimated the relationship between consumption of single food groups and phthalate levels.

Table S2 Bivariate linear regression models for association of potential confounders with muscle strength, power and size.

Based on bivariate linear regression models, all PFAS concentrations in nulliparous women were higher than in parous women (P < 0.1).

The distribution of each SES measure across other independent drivers of LOS was examined with bivariate linear regression models.

Possible associations between infant blood lead and the independent variables were separately explored with bivariate linear regression models.

Second, we assessed relationships between dietary intake of individual food types and measured levels of individual phthalate metabolites with bivariate analyses, including correlations and bivariate linear regression models.

For continuous predictors, bivariate linear regression models were computed with each type of euthanasia as dummy variables in order to show statistically significant mean differences.