Sentence examples for backward multivariable regression analysis from inspiring English sources

Variables associated with the univariable model at p < 0.1 were included in a stepwise, backward multivariable regression analysis, with a threshold for variable retention of p < 0.1.

Independent associations with GLS were assessed using stepwise multivariable regression analysis with backward elimination.

Subsequently, a multivariable regression analysis in combination with a backward selection strategy (α = 0.157), was performed to obtain the final model[ 13].

Finally, we conducted a multivariable regression analysis.

Multivariable regression analysis: adjusted for baseline covariates by traditional multivariable regression with stepwise variable selection.

With stepwise backward multivariable linear regression analysis we identified baseline predictors for change in MIF levels after treatment.

The relationship between TNFα expression and clinical response was confirmed by stepwise backward multivariable logistic regression analysis.

Stepwise backward multivariable linear regression analysis was used to identify possible baseline predictors of change in MIF levels at weeks 16 and 52.

Backward elimination multivariable logistic regression analysis revealed which factors remained significant after adjustment for other variables (Table 2).

Adjusted for significant confounders in each model from the following ones using backward stepwise multivariable linear regression analysis and GEE for adjustment for clustering : child age, sex, ever started school, intake of dark green leafy vegetables, intake of citrus, maternal literacy, maternal Raven's score, parity, asset score, history of diarrhea/dysentery, household salt iodine level.

Age, the number of synthetic disease-modifying agents (DMARDs) and total cholesterol concentrations were independently associated with plaque in multivariable stepwise backward regression analysis (odds ratio (95% confidence interval) = 1.15 (1.07 to 1.24), P <0.0001, 1.51 (1.05 to 2.17), P = 0.03 and 1.66 (1.00 to 2.73) P = 0.04), respectively).