Sentence examples for multivariate models adjusted from inspiring English sources

For survival analyses, proliferation markers were modelled as continuous or dichotomous according to the relative fit of multivariate models adjusted for the standard prognostic factors, assessed using likelihood ratios.

The average difference in CD4+ T cell counts was up to 273 cells less among women with lesions at all three visits in the crude models compared to women in asymptomatic group (Table 3) but only up to 51 cells less in the multivariate models adjusted for baseline CD4+ T cell count (Table 4, trend p-value <0.001).

Multivariate models adjusted for selected demographic and risk variables known to be associated with HIV risk and disease progression as well as variables that were statistically different in crude comparisons and included age, race, injection and noninjection drug use, number of lifetime sexual partners, use of herpes medications and antiretroviral therapy, as well as baseline CD4+ T cell count.

All multivariate models adjusted for age, religion and education level.

Third, the multivariate models adjusted for clustering or correlation of responses within the same facility [ 20].

In case of unbalanced characteristics, multivariate models adjusted for baseline characteristics will be performed.

METHODS: We compared presurgery symptoms and treatment outcomes between patients with and without diabetes using univariate and multivariate models, adjusting for demographics and comorbidities.

In multivariate models adjusting for duration of diabetes, systolic blood pressure, cigarette smoking, serum glucose, Cerebrovascular Risk Factor Scale, Cumulative Illness Rating Scale, and retinopathy levels, this relationship remained significant for retinal arterioles (p =.02) but not for retinal venules (p =.10).

In addition, the interaction of both polymorphisms remained statistically significant in multivariate models adjusting for clinical prognostic factors.

There was no significant trend in multivariate models adjusting for other covariates (p for trends > 0.53) (Table 5).

We also made multivariate models adjusting for age, civil status, educational level, COCs use, hormone use, family history of gynaecological cancer, physical activity, and BMI.