Sentences with word «covariate»

Demographic variables that differed among conditions were included as covariates in subsequent analyses.

These analyses will account for covariates such as family history of atopy and infants» diet and will be assessed over the first year of life by a survival analysis approach.48, 49 Thus, this prospective design will also allow us to disentangle the relative contributions of genetic and nutritional aspects, as will statistical path analyses to test for a potential mediating effect of PUFA levels among genotypes and AD development.50

While selection bias is still a concern, it is worthwhile noting that the authors control for a very rich set of covariates including student demographics, parental income, parental education, student AFQT score, freshman year GPA, state of birth and various school characteristics.

Multivariate analyses were performed with logistic regression for outcome variables with paternal depression and other covariates as predictors.

We looked at the mentioned associations in 3 different models with covariates as those mentioned above.

[The moderated regression models were retested using two health - related variables as additional covariates on Step 1, scores on a standard single item measuring self - rated health and a count of 17 health conditions for which the respondent had received physician diagnoses (e.g., arthritis, ulcers, emphysema).

How Bias Reduction Is Affected by Covariate Choice, Unreliability, and Mode of Data Analysis: Results From Two Types of Within - Study Comparisons.

To test Hypothesis II investigating the effects of parental depression variable on the strength of an association between intelligence and behavior adaptability, first - order interaction variables were created and entered along with demographic covariates in hierarchical regression analyses.

And, importantly, even models that are very strongly correlated — such as math value - added models with and without student covariates in (Panel B, r = 0.97)-- show considerable movement between quintiles.

We investigated substantial heterogeneity for all four outcomes with subgroup analyses for the following covariates: who delivered care, type of support, timing of support, background breastfeeding rate and number of postnatal contacts.

At step 1, we controlled for the respective T1 eating behaviour, and for potential covariates of maternal age, BMI and education, and child age and gender (1 = male; 2 = female).

Effects were estimated with the inclusion of baseline covariates.

Third, the analyses explore whether measured covariates account for associations with PAE.

We modelled age at risk as a time varying covariate, using Lexis expansion to stratify each participant into N observations, taking into account differing ages at risk over the follow - up period (14 - 16, 17 - 19, 20 - 22, 23 - 25, 26 - 27; Nmax = 5).

We used analysis of variance to compare the mean children's TV - viewing times across the 4 groups defined by maternal obesity and depression status (with and without covariate adjustments), and we used the Newman - Keuls test for pairwise comparison of group means.

Marital satisfaction differed across these venues [F (5, 2,381) = 6.42, P < 0.001](Table 2), and repeating the analysis using year of marriage, sex, age, educational background, household income, ethnicity, religious affiliation, and employment status as covariates did not change these results [F (5, 2,273) = 5.91, P < 0.001].

These associations were significant after adjustment for a number of important covariates known to be associated with vascular health, including lifestyle factors, medication use, and other nutrients.

We included relevant covariates in our regression models that may confound the relationship between breastfeeding experiences and postpartum depression.

Because the region provides information about a continuum of covariate values, the use of simultaneous statistical inference is required.28 - 30 In an approach similar to that taken by Olds et al, 6 we have extended the methods for simultaneous regions of significance to the generalized case, with log - link functions and Poisson error.

Assessing covariates of adolescent delinquency trajectories: A latent growth mixture.

Baseline covariate information was collected from the demographic questionnaire that was administered to the national opinion panel from which the sample was drawn.

After adjustment for covariate factors, the extent of depression at ages 17 to 18 years remained associated with later depression and suicidal tendencies.

The differences in percentage of marital break - ups across on - line venues approached statistical significance [χ2 (10) = 16.71, P = 0.08; Table S5], but differences across off - line venues were not statistically significant [χ2 (9) = 10.17, P = 0.34], and neither test was significant after controlling for covariates [χ2 (10) = 14.41, P = 0.17, and χ2 (9) = 7.66, P = 0.56, respectively].

For child BMIz, the model combining potential maternal and child covariates with T1 BMIz (step 1) was a significant predictor of T2 BMIz, explaining 25 % of the variance (R 2 =.25, p <.001).

Table 1 shows the prevalence of CMD and tertiles of reported sugar consumption from sweet food / beverages according to covariates at phase 3.

After control for multiple covariates, MAE accounted for 28 % of the alcohol onset and 20 % of the binge drinking transitions observed in this cohort, making it a risk factor with important public health implications and arguing for policy approaches to prevention of MAE.

These figures present models probing the significant interaction terms by presenting the figures of the interaction coefficients and 95 % confidence intervals when covariates are centered at a one standard deviation below the mean, the mean, and one standard deviation above the mean.

The authors assess how different covariates contribute to improving the statistical power of a randomization design and examine differences between math and reading tests; differences between test types (curriculum - referenced tests versus norm - referenced tests); and differences between elementary school and secondary school, to see if the test subject, test type, or grade level makes a large difference in the crucial design parameters.

While our data are fairly limited, and the results relatively imprecise, we find preliminary evidence that covariate choice matters, and that method choice matters, but perhaps only when comparing to a broader sample that includes students who did not apply to the program.

Covariates capturing parent characteristics included: (1) marital status using a dichotomised indicator of whether they were married / cohabiting or not; (2) employment status categorised into a binary indicator distinguishing whether the parent was in paid employment or not; and (3) presences of siblings whose youngest child was younger than 16.

Race, cohort, and maternal education were included as time - invariant covariates.

Pregnancy risk status was included in the model by treating each high - or medium - risk condition as a separate covariate.