Sentences with phrase «bivariate correlations»

Bivariate correlations between microaggressions frequency and depressive and somatic symptoms

A correlation matrix of study variables was produced in order to examine the bivariate correlations between risk factors and SDQ scores.

Bivariate correlations and simultaneous regression analyses indicated a unique pattern of predictors for attention - deficit / hyperactivity disorder, aggression, anxiety, and depression symptoms.

Bivariate correlations were run for all variables.

Bivariate correlations were computed to determine relationships of the dependent variable (adaptive behavior) with the aforementioned independent variables and possible demographic covariates based on the literature.

Bivariate correlations between observed parenting and adolescent adjustment (Table III) revealed that mothers» higher levels of observed collaborative parenting were related to significantly lower levels of externalizing problems in adolescents (r = −.24, p =.021) and somewhat fewer problems with quality of life (r = −.19, p =.074).

Bivariate correlations between familial risk to externalizing behaviors, perceived parenting styles and externalizing behavior

We also examined for effects of CU traits using a dimensional approach by testing for correlations between CU traits and EA, emotion recognition, and affective empathy (using either parametric or non-parametric bivariate correlations, as appropriate).

Table 2 reports the bivariate correlations among the variables in the model, before the directional hypothesized longitudinal path model was tested.

Descriptive analysis and a correlation matrix were used to indicate characteristics of the participants and bivariate correlations, respectively.

Third, bivariate correlations examined relations among the parenting scales, emotional, informational, and instrumental support, and depressive symptoms.

Pearson bivariate correlations for youth and parent BGMC questionnaire scores demonstrated stability across the period of 1 year: for youth BGMC, r = 0.60, P < 0.0001; for parent BGMC, r = 0.80, P < 0.0001.

Bivariate correlations among depressive symptoms, victimization, and marital dissatisfaction

Pearson bivariate correlations were used to examine the associations between the BGMC questionnaires and continuous variables (e.g., age, duration of type 1 diabetes, and A1c values).

Descriptive analyses examined the bivariate correlations between the study variables.

To test our final hypothesis, that parenting would mediate the effects of marital status on adolescent adjustment, we first calculated bivariate correlations to determine the associations between parenting behaviors and adolescent adjustment variables (CBCL and YSR composite score, quality of life, and HbA1c).

Fourth, we calculated bivariate correlations among all model variables.

Bivariate correlations are shown for the purpose of clear visualization and interpretation.

The means, standard deviations, and bivariate correlations among the model variables are summarized in Table I. Correlations among the predictors of engagement were modest and do not suggest the presence of multicollinearity.

Bivariate Correlations among Self - reported Depression, Loneliness, and Perceived Social Acceptance

The bivariate correlations were used to (a) check for multicollinearity among predictor variables and (b) determine whether any error terms needed to be correlated in the final model.

In line with earlier studies [9, 26, 43], we found FR - EXT to be a risk factor for externalizing behaviors in preadolescents, as evidenced by significant bivariate correlations between FR - EXT and all seven dependent measures of externalizing behaviors.

First, exploratory analyses using bivariate correlations and independent - samples t - tests were run to assess how well the three PCERA scales related to other parental and child attributes also collected at hospital discharge (Table II).

Descriptive Data for the Measures Included in the Model — Means, Standard Deviations and Bivariate Correlations by Sex.

Subsequently, attachment mechanisms in early childhood were compared to these indices of national attachment, yet the study confined itself to analysing bivariate correlations.

Bivariate correlations between TL - BS parameters for each emotional face, CU traits, anxiety and ODD - related problems.

Table 2 shows descriptive statistics for children's DBD symptoms (i.e., CP and ADHD symptoms) and CU traits, and parental emotion socialization variables; as well as the bivariate correlations among these variables.

Interrater agreement was calculated using bivariate correlations between diagnosticians (r =.70).

Interrater reliabilities were calculated using bivariate correlations which ranged from r =.58 to r =.78 (M =.70; SD =.07), indicating high overall interrater reliability.

Mean scores, standard deviations (SDs) and bivariate correlations between the variables at pre-test (N = 42).

The convergent validity is a form of validation that tests for the association between a construct measured by a scale and other measures that theoretically related to this construct.31 32 For the convergent validity of the ASSET subscales, a set of variables used in the survey of the project were selected, and bivariate correlations were computed (online supplementary table 2).

The results of the bivariate correlations show that the PWB subscale and the MHI - 5, SHS and CD - RISC scales correlate significantly and in the expected direction (table 5).

Finally, the analysis of the remaining bivariate correlations allows for the following considerations.

Mean (s.d.) scores and bivariate correlations for time 1 and time 2 maternal feeding practices and child eating behaviour (N = 156)

Bivariate correlations were examined between the CFPQ and attitude measures (i.e., concern about the child being overweight, concern about the child being underweight, and parental feelings of responsibility toward child feeding, Table IV).

Descriptive statistics and bivariate correlations for child - and school - level variables

Bivariate correlation matrices of dependent and independent variables, by district

A bivariate correlation was run to assess the relationship between the fourteen paternal involvement and nurturance variables (Table 3).

Hypotheses were tested using bivariate correlation procedures and regression analyses.

A series of bivariate correlation with Pearson test was carried out to analyze correlations between TAS - 20 and ASQ factors and their children's SAFA - A, D, and S scores.

Not exact matches

The bivariate approach is the foundation of if - then analysis, highlighting the link between the cause and the effect variables and any real correlation.

Studying bike lanes in 90 or the 100 largest American cities, Pucher and collaborater Ralph Buehl used Pearson's correlation, bivariate quartile analysis, and two different types of regressions to measure the relationship between more and longer bike lanes and quantity of cyclists.

The algorithm measures 2 - D correlations by looking at 0th & 1st & / or 1st & 2nd (i.e. adjacent) derivatives to extract empirical bivariate phase information at variable bandwidth.

if you've got a bivariate random parameters (intercepts and age effects) up and running, and so can estimate a correlation or covariance between initial growth rate (the tree - specific random additive effect at age = 1) and tree - specific random age coefficient across the sample, the significance of that correlation / covariance would be a first crack at this without choosing an age at which to split the sample.

Zero - order correlation analyses were conducted to test bivariate associations between the predictor and criterion variables.

We calculated χ2 statistics, t tests, and correlation coefficients to analyze the bivariate associations between each potential predictor variable (anthropometric and psychosocial family characteristics) and the 2 criteria of long - term weight change: success versus failure in weight reduction up to the 12 - month follow - up and weight change between the conclusion of treatment and the 12 - month follow - up.

For each analysis, bivariate associations were calculated as tetrachoric correlations.

We first ran bivariate and point - biserial correlations between the variables that showed significant group effects and IQ, SES, and psychiatric comorbidity.

Bivariate relationships among predictors and outcomes were assessed using Pearson product moment or Spearman rank order (for relationships with screen time) correlation coefficients.

To test for associations among the various measures, we used one - tailed, bivariate Pearson's correlations, which measure the strength and direction, as well as the significance of linear relationships between pairs of variables.