Sentences with phrase «for dichotomous variables»

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.

Group contrasts for continuous measures relied on unpaired t tests, uncorrected χ2 for dichotomous variables, and Fisher exact tests when expected cell frequencies were less than 5.

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.

(Table 5) was for the dichotomous variables.

Not exact matches

To facilitate presentation of the final model, dichotomous variables were constructed for these factors (ie, goal ≤ 26 weeks or > 26 weeks and maternal age ≤ 30 years or > 30 years).

where Yis alternatively represents an outcome — academic achievement, cognitive ability, and academic effort — for the ith child and in school s. Asianis is a dichotomous variable indicating that child i is Asian (vs. white).

For the first analysis seven dichotomous variables (yes / no) were created to see if either the intervention or control identified any of the seven dental abnormalities.

To generate predicted probabilities, we held all variables at their means (or modal values if dichotomous) aside from the difference in readability score variable, which we varied from -4 to 4 based on the spectrum of our data.102 The results for the predicted probability that a moving party prevails on a motion for summary judgment based on a given readability score are presented in Figure 1 below.103

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.

We include both African American and non-Hispanic Caucasian males in our analytical data set (we include a dichotomous dummy variable controlling for race).

We created a dichotomous variable for scores in the top 10th percentile versus lower.

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

Generalized regression models (logistic regression for dichotomous outcomes, linear regression for continuous outcomes) were used to estimate the overall adjusted effects of Healthy Steps.26, 27 These models included site variables to account for the fact that families within sites tend to respond more similarly than those at different sites.

The final model combined growth factors for both dichotomous and continuous variables into a two - part model.

Non-linear slope factors for the dichotomous and continuous alcohol use variables provided a good fit the data.

For the purpose of clinical interpretation, however, a dichotomous variable was also created to identify those children scoring at or above the 90th percentile for this sampFor the purpose of clinical interpretation, however, a dichotomous variable was also created to identify those children scoring at or above the 90th percentile for this sampfor this sample.

For the slope factor of the dichotomous variables, the first three factor loadings were fixed and the last four were freely estimated -LRB--2, -1, 0, 0.26, 0.64, 0.93, 1.26 for W1 - W7, respectivelFor the slope factor of the dichotomous variables, the first three factor loadings were fixed and the last four were freely estimated -LRB--2, -1, 0, 0.26, 0.64, 0.93, 1.26 for W1 - W7, respectivelfor W1 - W7, respectively).

We centered each continuous moderator variable around its mean and for the categorical variables we made dichotomous dummy codes.

Non-linear slope factors provided a good fit to the data for both the dichotomous and frequency marijuana use variables.

Loadings for the slope factors were constrained to the estimates from the unconditional models and covariances between the growth factors for the dichotomous and continuous variables were estimated.

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.