Sentences with phrase «of hierarchical regression analyses»

Summary of hierarchical regression analyses for children's birth status and children's sustained selective attention performance predicting children's problem behavior, as reported by mothers and teachers

A series of hierarchical regression analyses were performed to test whether the influence of early infant behavioral characteristics on later parenting stress and temperament ratings would vary depending on factors in the infant — parent dyad.

Summary of hierarchical regression analyses predicting rumors in the fall and spring of 6th grade

Summary of hierarchical regression analyses testing peer - and teacher - reported popularity among boys as a mediator of the link between pubertal timing and rumors

Final results of hierarchical regression analyses for time to complete and number of excess moves on Tower of London task.

Table 2 presents the results of the hierarchical regression analyses.

Result of hierarchical regression analysis (dependent variable: process innovation performance).

The results of the hierarchical regression analysis are presented in table 5.

Model 1 of each hierarchical regression analysis contained a block of demographic variables including parent and child gender, parent's childhood SES, age at parenthood, current family SES, and neighborhood risk.

Not exact matches

Specific statistical areas of expertise include factor and cluster analysis, basic bivariate analyses, repeated measures analyses, linear and hierarchical / mixed models, structural equation modeling, and nonparametric analyses including logistic regression techniques.

Three analyses were conducted with the cross-sectional data using teachers» WSS ratings of student achievement and students» WJ - R standard scores: a) correlations comparing the students» standard scores on the various subtests of the WJ - R and the WSS checklist and summary report ratings of student achievement within the corresponding WSS domains, b) four - step hierarchical regressions examining the different factors that accounted for the variance in students» spring WJ - R scores, and c) Receiver - Operating - Characteristic (ROC) curves, which make possible a determination of whether a random pair of average and below - average scores on the WJ - R would be ranked correctly in terms of performance on the WSS.

Contrary to expectation, the presence of painful symptoms in patients was not statistically significantly associated with partners» psychological distress in the hierarchical regression analysis, despite 65.1 % of partners having reported the presence of painful symptoms in the patient.

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

An examination of collinearity was undertaken comparing changes in the standard errors and magnitude and sign (positive or negative) of the bivariate analyses results with the standard bivariate regression models for each sex and the full hierarchical regression models.

Hierarchical regression analyses were computed to determine the impact of predictor variables — age, gender, SES and ECE attendance.

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

RESULTS: Hierarchical regression analyses revealed that long - term success (at least 5 % weight reduction by the 1 - year follow - up) versus failure (dropping out or less weight reduction) was significantly predicted by the set of psychosocial variables (family adversity, maternal depression, and attachment insecurity) when we controlled for familial obesity, preintervention overweight, age, and gender of the index child and parental educational level.

In hierarchical regression analysis of SA, social support was present in models 2 and 3, but disappeared after adjusting for substance use and depressive symptoms in model 4 (table 3).

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.

Data analyzed using zero - order correlation and hierarchical regression analysis showed positive correlations of POS and job satisfaction with work performance, and also showed independent and joint positive associations of POS and job satisfaction with OCB and each of its four dimensions.

Prior to conducting the main analysis of hierarchical regression, the data were checked for outliers that might show undue influence in some analyses.

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.

Analysis involved correlations, hierarchical multiple regression and analysis of vAnalysis involved correlations, hierarchical multiple regression and analysis of vanalysis 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).

Hierarchical regression analyses indicated that gender (females were less likely to be employed), IQ (lower IQ associated with unemployment), and transportation dependence accounted for 42 % of the variance in employment.

Independent sample t - test was used to compare the level of self - esteem, family function score and social support score between the two groups with and without grandparenting experience; Pearson correlation was calculated to explore how levels of self - esteem and family functions as well as perceived social support were related; Hierarchical regression analysis was applied to examine the moderating effect of social support on the relationship between family function and self - esteem.

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.

Means and Standard Deviations of General Liking and Romantic Attraction as a Function of Availability, Commitment, and Sociosexuality Predicting the Target s General Likability: Hierarchical Regression Analyses Predicting Romantic Attraction toward a Target: Hierarchical Regression Analyses.

She has technical expertise in a wide range of statistical techniques used in the social sciences, including structural equation modeling, confirmatory factor analysis and MIMIC approaches to measurement, path modeling, regression analysis (e.g., linear, logistic, Poisson), latent class analysis, hierarchical linear models (including growth curve modeling), latent transition analysis, mixture modeling, item response theory, as well as more commonly used techniques drawing from classical test theory (e.g., reliability analysis through Cronbach's alpha, exploratory factor analysis, uni - and multivariate regression, correlation, ANOVA, etc).

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.

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

Hierarchical regression analyses were conducted to examine the effects of friendship quality on the adolescents» well - being as a function of country and hearing status.

Hierarchical regression analyses were used to examine relations between contingent responsiveness and child compliance, after accounting for the quality of parent directives and parent negativity.

Hierarchical regression analyses were conducted to examine the effect of pc use with a friend, country, hearing status, school setting and age on the online, mixed and offline friendship quality.

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.

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 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).

To test both questions, hierarchical regression analyses were performed with demographics entered in block one of each model, the mindfulness subscales entered into block two, and one conflict style entered as the criterion variable for each model.

By using... hierarchical regression analyses potential moderating influences of self - reported trait - mindfulness and trait values of general psychological stress reactivity on stress protective effects of a three months Taiji training were examined.

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.

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

The hierarchical regression analyses done in the second part of the study indicated that age, gender, and individuation dimensions are important predictors of romantic attachment dimensions.

The first hierarchical regression analysis investigated the moderating effects of parental and school support on the relationship between peer - victimization and mental health, while considering gender.

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.

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.

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.

A three - step, hierarchical regression analysis was performed to predict change in generalized anxiety from cognitive vulnerabilities, sub-dimensions of psychological well - being, and their interaction (as well as T1 generalized anxiety).

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.