Sentence examples for multiple hierarchical regression from inspiring English sources

Multiple hierarchical regression analyses revealed that the subjects' confidence in their ability to perform a range of tasks despite pain (assessed at baseline), was predictive of total pain behaviour and avoidance behaviour over the nine-month study period.

After controlling for demographic variables including race, gender, age, and BMI, multiple hierarchical regression analyses revealed that morning IL-6 levels accounted for a significant portion of the variance of REM latency (p < .01), sleep efficiency (p < .01), and % WASO (p = .01).01

When adjusted for depression, helplessness, and magnification scores, a multiple hierarchical regression analysis revealed that younger age (β = −.247, P < .005), previous chronic pain (β = .175, P < .05), presurgical anxiety (β = .235, P < .05), and the rumination component of pain catastrophizing (β = .222, P < .05) were significant predictors of APSP intensity.

In a cross-sectional correlational design, data from a prior study of 141 insulin-requiring adults with type 1 or type 2 diabetes were examined using descriptive statistics, Pearson's correlation, and multiple hierarchical regression.

The hypothesis was tested using multiple hierarchical regression analyses.

The lifestyle parameters were evaluated using multiple hierarchical regression and binary logistic regression.

Multiple hierarchical regressions were used to examine general and specific ER as predictors of depressive symptoms at follow-ups.

Multiple hierarchical linear regression analysis was used, controlling for NSSI frequency and gender.

Multiple and hierarchical regression analyses showed that the TPB model significantly predicted intention to perform both dietary behaviors and intention significantly predicted both behaviors.

All variables except caffeine and exercise habits were evaluated using both multiple linear hierarchical regression and binary logistic regression.

All variables that were statistically significantly associated in the bivariate analysis (Table 3) were entered into the multiple linear hierarchical regression models.