Sentences with phrase «as dichotomous variables»

Because they presented bimodal distributions, the hospitalization and injury outcomes variables were analyzed as dichotomous variables with logistic regressions using the same hierarchical model design.

This variable was coded as a dichotomous variable with a Likert score of 1 — 3 indicating «disliked breastfeeding» and a Likert score of 4 — 5 indicating «liked breastfeeding.»

Hyperreactivity was analyzed as a dichotomous variable at two cutoff points (PC20 of 8 mg per milliliter or less or PC20 of 16 mg per milliliter or less).

These included age (in years), gender (1 = male, 2 = female), education (1 = less than high school, 2 = high school diploma or equivalent, 3 = some college / vocational education, and 4 = college education or higher), and ethnic background (coded as a dichotomous variable, 1 = White vs. 2 = non-White).

In the analyses that follow, the maternal affective disorders variable was used as a dichotomous variable that represents whether a subject's mother ever had an affective disorder (yes or no).

Engagement was measured as a dichotomous variable, «engaged» or «not engaged.»

Not exact matches

107 Figure 2, which is based on Models 2 and 3 in Table 4, was derived similarly to Figure 1 by setting continuous variables to their mean values, dichotomous variables to their modal levels, and ordered variables to their median values, as well as varying the readability score variable from -3 to 3, which is the approximate range of values in our dataset.

This assumption reflects the fact that the moving party controls whether to file a motion in the first place, and is consistent with the data suggesting that moving parties have a greater than 50 % success rate in federal court.96 To test this assumption, we coded a dichotomous dependent variable as 1 if the moving party prevailed on the motion and 0 otherwise.

As shown in Table 5, the score and dichotomous variable (0 = non-clinical, 1 = clinical), internalizing problems was significantly associated with: child's age (β = 0.42), mother's age (β = − 0.32), currently visits to their father (β = 0.56), mo - ther's anxiety (β = 0.63), and the number of years the child lived with the father in the past (β = − 0.32).

Based on past work, 17,18 responses were assigned a score (0 for never or not in the past year, 1 for event occurred once, 2 for twice, 4 for 3 — 5 times, 8 for 6 — 10 times, 15 for 11 — 20 times, and 25 for > 20 times), and we created a dichotomous variable considering domain scores in the top 10th percentile as high risk for maltreatment.

The number of adverse childhood experiences was summed for each respondent (range, 0 - 8); analyses were repeated with the summed score as an ordinal variable (0, 1, 2, 3, 4, or ≥ 5) or as 5 dichotomous variables (yes / no) with 0 experiences as the referent.

Thus, analyses were conducted with the summed score as 7 dichotomous variables (yes / no), with 0 experiences as the referent.

Specifically, the relation of mother's remission status to change in CBCL score was modeled so that the change score was treated as the dependent variable, with mother's remission status as a dichotomous independent variable, and with the baseline value of the CBCL score and the mother's baseline HRDS as covariates.

A dichotomous depression symptoms (probable and major) variable was defined as EPDS score ≥ 13.

Variables were included in the analyses as dichotomous measures.

The estimated effects of continuous outcomes are presented as a standardised effect size and dichotomous variables as OR.

The baseline covariates serve as adjustment for potential differences between intervention and control families that resulted from nonrandom assignment at quasi-experimental sites or selective reporting of outcome data.29 Results of these adjusted analyses are reported as ORs for dichotomous variables and as differences in means for continuous outcomes.

Binary logistic regression was employed for multivariable analysis, as the dependent variable was dichotomous.

Because previous research (Gilligan et al., in press; Suitor et al., 2009) has shown that the perception of any favoritism, rather than the particular pattern (e.g., mother preferred the respondent or another child), predicted sibling tension, we used the children's responses to create a dichotomous variable: 0 = child does not perceive mother as preferring any particular offspring as her future caregiver and 1 = child perceives that mother prefers either him / herself or another child as her caregiver.

As the outcome of interest — removal from the classroom through either suspension or expulsion — was a dichotomous variable, a logistic regression was most appropriate.

The dichotomous variable of having a late versus earlier preterm infant was examined as an alternative to neonatal risk, but there were no significant differences in the findings, and thus, the continuous neonatal risk variable was used in the final models.

The internalizing x externalizing interaction factor was a statistically significant predictor of the intercept for dichotomous variables when it was specified at W1, W2, W4, and W5, βs = − 11.80 to − 3.23, ps < 0.05, and the nature of this interaction was similar to that described in our main analysis with W3 specified as the intercept.

A third model with the same predictors and random effects was performed with the FaceReader measure of disgust as dichotomous outcome variable.

No gender differences were found with respect to attachment to mother (χ 2 (1) =.003, p >.05) or father (χ 2 (1) =.26, p >.05), nor were there any effects of child age (entered in a logistic regression with dichotomous attachment classification as outcome variable) for mother B =.02, p =.67 and father B = −.03, p =.49.