Sentences with phrase «multiple hierarchical regression»

Summary of Multiple Hierarchical Regression Analyses Predicting Parent Satisfaction at 6 Months

Multiple hierarchical regression analyses showed that a higher level of QOL was predicted by higher levels of psychological flexibility and social connectedness, while controlling for symptom severity.

Summary of Multiple Hierarchical Regression Analyses Predicting Parental Nurturance at 6 Months

Therefore, given that only these four parameters were significantly associated with CU traits and ODD problems (teacher rate), we further conducted four separate multiple hierarchical regression analyses, one for each of these parameters, in order to examine the contributions of CU traits, anxiety, ODD - related problems and their interactions on attentional processing of emotional faces as indexed by these parameters.

In order to test the potential moderator effect between negative affectivity and effortful control on ODD - related problems, we conducted two separate multiple hierarchical regression analyses, one for the parental and the other for the teacher rate of ODD - related problems.

Keywords: Supervisor support, supportive work atmosphere, job demands, job control, job content, self - esteem, mistrust, multiple hierarchical regression analyses

Multiple Hierarchical Regression showed that state gratitude and institutional gratitude uniquely predict job satisfaction.

Not exact matches

Hierarchical multiple regression analyses were used to adjust for the four confounding factors shown in Table 1.

Hierarchical Multiple Regression Analyses Predicting Depression, State and Trait Anxiety, Externalizing and Internalizing Behavior Problems in Children With Rheumatic Diseases

Correlations and hierarchical multiple regression analyses were performed.

In Step 3, we conducted hierarchical multiple regressions on each of the adjustment variables.

To clarify the nature of these interactions, we ran two additional hierarchical multiple regression analyses by entering the demographic / disease severity variables, followed by daily hassles, the specific social support source of interest (classmate or teacher), and the relevant interaction between hassles and social support (classmate or teacher).

Summary of hierarchical multiple regression analyses (stepwise method) examining multivariate correlates of SA

Hierarchical multiple regressions were used to test whether maternal feeding practices could predict changes in child eating behaviours over time.

Hierarchical multiple linear regression analyses were conducted to test whether the income - to - needs ratio predicted brain volumes.

Summary of hierarchical multiple regression analyses (stepwise method) examining multivariate correlates of DSH

To test the hypothesis, Muise conducted an online survey with 308 respondents, age 17 to 24, and used hierarchical multiple regression analysis, controlling for individual, personality and relationship factors (to tease out what's Facebook's contribution to jealousy).

Two hierarchical multiple regressions were calculated, both of which included estimated METs per week, mean choice reaction time, age, and gender as predictors at the first level and the five NEO-FFI scores at the second - level.

Analysis involved correlations, hierarchical multiple regression and analysis of variance.

Hierarchical multiple regression analyses indicated that commonly investigated psychosocial factors such as affectivity, coping, and social support moderated the relationship between perceived stress and one illness behavior (report of illness without visits to the doctor).

The hierarchical multiple regression analyses were conducted in each group.

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 other 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 other 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.

Drawing on three waves of data collected from an ethnically diverse sample of middle school girls (n = 912), hierarchical multiple regression analyses revealed that more advanced development at the start of middle school predicted peer - and teacher - reported popularity as well as increased risk of being targeted for rumors.

Models with dysfunctional emotion regulation as a mediation variable were tested via hierarchical multiple regression analyses and bootstrapping procedure.

A model with cognitive efficiency as a mediator variable was tested using hierarchical multiple regression analysis, with a bootstrapping procedure to examine indirect effects.

Hierarchical multiple regression analyses were calculated to evaluate the predictive power of the WoC factors for marital satisfaction factors.

Hierarchical multiple regression analysis of the total sample revealed that the combination of demographic variables, parental monitoring, television - viewing habits, and exposure to violence explained 45 % of students» self - reported violent behaviors.

Hierarchical multiple regressions, controlling for age and gender, were used to predict prosocial behaviors and emotional symptoms, and test the moderating role of individual protective factors.

Hierarchical Multiple Regressions Predicting 4 - Month Parenting Stress (β's Denoted for Each Step in Model)

To examine the relation between multiple measures of diabetes - specific family factors and control, we conducted a hierarchical multiple linear regression in SPSS 11.0 (SPSS, Inc., 2001).

Third, hierarchical multiple regressions were conducted to examine whether (1) relationship quality variables were associated with outcomes independently of sociodemographic characteristics, and (2) ethnicity moderated relations of parental acceptance or conflict with diabetes management and depressive symptoms.

Hierarchical multiple regression analyses predicting maternal gatekeeping from mothers» ambivalent sexist attitudes

Third, to determine which fine - grained temperament traits were associated with internalizing and externalizing problems, hierarchical multiple regression analyses were performed in SPSS version 19.

Preliminary analyses were conducted to test for relations between demographic variables and study variables (HbA1c, adherence, and family functioning) for purposes of control in subsequent hierarchical multiple regression.

Hierarchical Multiple Regression Predicting 4 - Month Maternal Ratings of Infant Distress to Limitations (β's Denoted for Each Step in Model)

Results of a hierarchical multiple regression analyses showed that wives» perceptions of husbands» rejection predicted children's perceptions of maternal rejection, as well as — but to a significantly lesser extent — children's perceptions of paternal rejection.

Hierarchical multiple regressions were used for the main analyses.

Hierarchical multiple regressions were performed for nonemergency services, ER visits, ear infections, and acute respiratory illnesses, as they were continuous outcome variables.

Results of hierarchical multiple regressions indicated that sibling attachment uniquely influenced conflict and cooperation in the sibling relationship even after controlling for the effects of attachment to mothers, fathers and peers, as well as the reported warmth between siblings.

Hierarchical multiple regression analyses showed that dispositional social evaluative anxiety was uniquely positively associated with boys» and girls» social aggression and negatively associated with boys» overt aggression.