Sentence examples for the third multivariate model from inspiring English sources

We also repeated the third multivariate model using this subsample.

Associations between risk markers and phylloquinone and menaquinones intakes (both modeled continuously per 50 and 10 μg) were assessed by linear regression using the third multivariate model in the baseline random sample.

In the second multivariate model, C-reactive protein (OR 1.27, 95%CI 1.04 1.56) but not copeptin (OR 1.39 (95%CI 1.0 1.94), p = 0.05), remained associated with death or hospitalization, (For detailed values, see Table 4c).

For the first multivariate model the sex, age, area of living, education, marital status, physical exercise, alcohol use, and the BDI in addition to the GSS were entered as independent explanatory variables, whereas for the second multivariate model the GSS was replaced by the six items of which the GSS is comprised.

Of the non-seasonal explanatory variables, the same ones remained to be of significance in a similar way in the second multivariate model than in the first one, except the area of living which lost the significance.

In the second multivariate model, individual characteristics were added, which substantially improved model fit.

In the first multivariate model, adjustment was performed for age, sex and centre of inclusion.

The first multivariate model included each determinant and country of recruitment.

Results were similar for the bivariate models and for the first multivariate model whether we used complete or imputed data.

All the variables which were significantly associated with QOL in a linear way at the univariate analyses previously described, were included as covariates in the first multivariate model.

For the outcome of mortality, in the first multivariate model, KPC status was associated with increased odds of mortality, (OR 3.79, 95% CI 1.00 – 14.34; Table  5).