Sentences with phrase «variables at baseline»

The intercorrelations among the variables at baseline are shown in Table II.

Analysis of demographic and behavioral variables at baseline indicated no significant differences between the two groups.

The groups did not differ on any other variables at baseline.

In addition, there were no differences among conditions on outcome variables at baseline.

Not exact matches

Baseline crying and other background maternal and demographic variables will be recorded at home.

CIRES and NOAA researchers and their colleagues analyzed long - term observations of snow cover and meteorology at the NOAA Barrow Atmospheric Baseline Observatory outside of Utqiagvik (formerly Barrow), Alaska, along with other records of environmental variables in the region.

Currently, the best measurements of those variables come from a system called very - long - baseline interferometry (VLBI), which uses radio dishes spaced across Earth to stare at quasars — brilliant beacons in the distant universe that occasionally flicker.

Characteristics of the partially recovered autopsy cohort are shown in table F in appendix; the intervention and control groups were well balanced at baseline, with no evident differences for any demographic, clinical, or laboratory variables.

Further adjustment for other dietary variables potentially related to inflammation (intakes of saturated fat, omega - 3 fatty acids, vitamin C or E, β - carotene, lutein and zeaxanthin, and coffee or fish consumption) and physical activity at baseline or postsecondary school qualification did not affect the results (data not shown).

For example, if nuclear is providing 20 % of electric generation, it can be run at steady baseline, maximizing fuel efficiency, while all the other variable demand can be met with solar and wind based power that has been fed into storage systems during the peak periods.

When comparing HT and MBSR groups at baseline, χ2 tests revealed no significant differences in gender (P =.99), ethnicity (P =.32), age (P =.45), nor any study variables of interest (P =.10 — .99).

Since we found baseline differences in race / ethnicity and clinic site by treatment group, we also conducted multivariate analyses to control for these variables on outcomes including EC use, unprotected intercourse, contraceptive method change, frequency of condom use, and condom use at last intercourse.

An analysis of covariance (ANCOVA) was performed to study the intervention effects on the dependent variables (ie, the GHQ items and the two subscales of the PSOC) by examining differences between the intervention and control group at follow - up, controlling for baseline measures.

Consistent with a hypothesis that data are missing at random, several baseline demographic, but not outcome, variables predicted missingness including marital status (odds ratio [OR] = 3.4), parent age (OR = 0.92), child age (OR = 1.96), and non-white or Hispanic race / ethnicity (OR = 2.6).

Initial analyses examined potential differences in participant characteristics and demographics across intervention groups at baseline by using independent samples t tests for continuous variables and χ2 analyses for categorical variables.

No differences in demographic variables were found between PTG and WL at baseline or follow - up.

Five self - report questionnaires will be used at baseline and, except for the sociodemographic variables, after the intervention is completed (12, 18 and 24 months later) to evaluate the short - term and long - term effects of the intervention on primary (health) and secondary (social participation, life satisfaction and healthcare services utilisation) outcomes and to describe the participants (table 1).

To assess potential confounding, we examined group differences between sociodemographic variables and basic needs at baseline.

No enrolled family had missing data at baseline for these variables.

To analyze whether baseline psychosocial variables can be used to predict weight change up to a 12 - month follow - up examination in children and adolescents who attend a «best - practice» routine - care lifestyle intervention, we conducted a longitudinal analysis with 3 assessment waves: at baseline (T0: within 3 weeks before the start of the intervention) body weight and height of participants and family members and the psychosocial family characteristics were assessed; at the conclusion of the program (T1: 1 year after T0) and 1 year after conclusion (T2: 2 years after T0), body weights and heights of participants were reassessed.

Lack of access to early trauma and family dysfunction variables as well as measures of general cognitive impairment at baseline.

In addition, at baseline, we did not have access to early trauma or family dysfunction variables.

No differences were found between those who were retained and those who were missing at T2 for any of the baseline variables.

Baseline drinking status (ever vs never tried alcohol) did not predict attrition, but to account for attrition bias related to other variables, estimation was carried out after multiple imputation using the standard missing at random assumption (ie, missing data are assumed missing at random conditional on observed predictors included in the model).27 The imputation model included all the predictors in the alcohol models plus a number of auxiliary variables that were not of direct theoretical interest but were nonetheless predictive of missingness so as to improve the quality of the imputations and make the missing at random assumption more plausible.28

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.

Next, a logistic regression was conducted to test whether MDD diagnosis at baseline predicted MDD diagnosis at follow - up (12 and / or 24 months after baseline) while statistically controlling for demographic variables, comorbid diagnoses (split into separate disruptive and anxiety categories), stressful life events, and maternal and family history of affective disorders at baseline.

(3) As reported in the previous analysis, no differences were found between the experimental and control groups in a wide range of social, family, and parental variables assessed at baseline.

The three treatment conditions were comparable on all child and parent demographic and outcome variables collected at baseline.

Cancer - specific stress at baseline was examined as a predictor of psychological (cognitive - affective depressive symptoms, negative mood, mental health quality of life) and physical functioning (fatigue interference, sleep problems, physical health quality of life), controlling for demographic and treatment variables.

All of the variables were measured at baseline, except infant temperament, which was measured when the infants were 6 months old.

To examine whether the BI-anxiety relationship was moderated by any of the family environment variables and to assess whether each family environment variable predicted anxiety at follow - up after controlling for BI as well as baseline anxiety, the above logistic regressions were repeated, this time including BI group and the interaction between BI group.

To examine whether the BI-anxiety relationship was moderated by any of the family environment variables and to assess whether each family environment variable predicted anxiety at follow - up after controlling for BI as well as baseline anxiety, the above NB regressions were repeated, this time including BI group and the interaction between BI group.

Demographic and disease - related variables measured at baseline are referred to as level 2 variables because they reflect individual difference variables associated with the person.

For the latter variable, our final model may have been different if it had been measured at baseline.