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Data of birth outcome and results on clinic examination in adulthood were analyzed using analysis of variance and multivariate ordinal regression to estimate the association between birth weight and MetS.
In a randomly selected cohort (n = 599), a multivariate ordinal regression model selected resting heart rate, plasma glucose and hypertension as significant independent predictors for presence of albuminuria at any degree (table 3).
Third, bivariate and multivariate ordinal regression models of life expectancy on the studied variables were conducted.
Finally, a multivariate ordinal regression analysis was performed; results were expressed as odd ratios (OR) and 95% confidence intervals (CI).
Table 4 shows the results of the multivariate ordinal regression analysis for each of the five domains of the QOL instrument.
Subsequently, univariate and multivariate ordinal regression models were used to identify determinants of NVP severity in the 1st trimester of pregnancy.
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As aforementioned, univariate and multivariate ordinal regressions were used to examine the association between the number of self-reported protective behaviours (the dependent variable) and a range of cognitive, personal and contextual characteristics.
Multivariate ordinal logistic regression and linear regression were used to model the associations between covariates and the number of drugs received.
Those 8 factors that have statistical significances in single factor ordinal logistic regression analysis are entered into multivariate ordinal logistic regression analysis.
Those factors that have statistical significance in single factor ordinal logistic regression analysis are entered as multivariate ordinal logistic regression analysis.
In multivariate ordinal logistic regression analyses, adjusted for clustering at the school-level, only attitudes towards breakfast, parental descriptive norms and self-efficacy for eating breakfast were significantly associated with breakfast skipping.
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