Sentence examples for using a multivariable regression from inspiring English sources

Then expressions to calculate the combustion parameters have been obtained by using a multivariable regression fitting method.

The simulated results are then further processed by using a multivariable regression analysis on a group of dimensionless parameters as well as visualization with the scaling law on arcade structures to facilitate a design for arcade buildings that would enhance city breathability.

Relationship between ARF etiology and hospital mortality was assessed using a multivariable regression model adjusting for confounders.

The effect of coronary revascularization on the outcome of patients with and without AHF was assessed using a multivariable regression model.

This association remained non-significant after adjusting for predefined factors using a multivariable regression model (adjusted OR, 1.0; 95% CI, 0.8 1.3; P = 0.97; Table 4).

Indirect standardization develops risk adjustment using a multivariable regression approach.

Additionally, for each metabolite, we used a multivariable regression model that included genotype or haplotype, ln U-As), and adjustments for other variabln U-As

To avoid the bias from excluding patients with missing data (see appendix II on bmj.com for information on the proportion of missing values per study), we used a multivariable regression technique to impute missing values within each study.

For each metabolite (dependent variables), we used a multivariable regression model (using the general linear model) that included genotype or haplotype (as categorical variables) and ln U-As) (as a continuous and independent variabln U-Asderive p-vasues for assocontinuousf genotypes or handotypes windependenttabolite.

To study the prognostic value of the degree of temporal summation regarding changes in DAS28-CRP simultaneously accounting for the level of inflammation (ie, summed USD score) we will use a multivariable regression model with both measures applied as main effects as well as their interaction (ie, 'crude model').

To estimate the effect of exposure to NO2 on HRV, we used a multivariable regression model adjusting for study site (random effects), age, education, self-reported diabetes, hypertension, smoking status, frequency of physical exercise, uric acid levels, and beta-blocker intake in the previous 30 days.