Sentences with phrase «significant hierarchical regression analyses»

Table 6 gives the results of the significant hierarchical regression analyses.

Not exact matches

The hierarchical regression analysis showed a significant association between greater resilience and lower psychological distress in step 2.

Specifically, hierarchical regression analysis performed showed significant associations between ECE and letter naming, fine motor skills, expressive language, and problem solving.

The results of Pearson correlation analysis and hierarchical regression analysis revealed a statistically significant rela - tionship between job and life satisfaction, even after controlling for demographic and socioeconomic variables.

As shown in the results of the Pearson's correlations and the hierarchical regression analysis, social support had a significant negative association with PTSD symptoms, and this finding is consistent with other researches.9 36 51 52 The level of PTSD symptoms was significantly and negatively correlated with the healthcare workers» scores for objective support and utilisation of support.

Using the first year women's panel data of Korea Women's Development Institute, a series of analyses including Hierarchical Multiple Regression were taken to examine the comparative influence of socio - demographic factors, factors of the interaction with spouse and factors of the interaction with family of origin, Findings of hierarchical multiple regression identified that the influence of interaction with spouse was high, and factors of interaction with family of origin had a significant influence on marital satisfaction even after controlling the influences of otHierarchical Multiple Regression were taken to examine the comparative influence of socio - demographic factors, factors of the interaction with spouse and factors of the interaction with family of origin, Findings of hierarchical multiple regression identified that the influence of interaction with spouse was high, and factors of interaction with family of origin had a significant influence on marital satisfaction even after controlling the influences of otheRegression were taken to examine the comparative influence of socio - demographic factors, factors of the interaction with spouse and factors of the interaction with family of origin, Findings of hierarchical multiple regression identified that the influence of interaction with spouse was high, and factors of interaction with family of origin had a significant influence on marital satisfaction even after controlling the influences of othierarchical multiple regression identified that the influence of interaction with spouse was high, and factors of interaction with family of origin had a significant influence on marital satisfaction even after controlling the influences of otheregression identified that the influence of interaction with spouse was high, and factors of interaction with family of origin had a significant influence on marital satisfaction even after controlling the influences of other factors.

In hierarchical regression analyses with the various ENRICH factor scores as dependent variables and job satisfaction as the independent variable in the first block, the two SSQ factors in the second block, and the WOC factors in the third block, between 24 and 38 % of the variance in seven of the nine ENRICH factors (not significant model for «Family & Friends» and «Marriage & Children») could be explained by the variation in all the independent variables with varying weight of the several independent variables (Table 3).

Eight significant predictors for psychological distress were retained with hierarchical multivariate linear regression analysis after controlling for gender: seven predictors (Passive Coping, Active Coping and Social Support — UCL), Self - criticism and Dependency (DEQ), Intrusiveness (IES) and Attachment Anxiety (ECR - R) were general psychological characteristics whereas only one infertility - specific characteristics (Need for Parenthood; FPI) had predictive value.

In total, four stepwise hierarchical regressions were performed: one predicting school absences and separate hierarchical regression analyses for each factor of the SASC - R because results of a multivariate hierarchical regression analysis were significant, Wilk's lambda, F (3, 62) = 6.24, p <.01.