Sentence examples for multivariate models models from inspiring English sources

Table  2 presents the adjusted ORs and 95% CIs for the three multivariate models (Models 1, 2 and 3).

We also constructed a second set of multivariate models (models II in Additional files 1, 2 and 3) adjusted for the same confounders and covariates.

Multivariate models: Model 1 ("base"): sex + age.

Further adjustment of the multivariate models (Model 1) for education, hypertension, and diabetes did not affect the risk estimates (data not shown).

We assessed whether the ethnic differences in OR for diabetes were significant after adjustments in multivariate models: Model 1: age, Model 2: age and adiposity (WHR) and Model 3: age, adiposity and SEP (body height, education and income-generating work), with Norwegians as reference.

The observation that inclusion of IL-6 and ICAM in multivariate models (Model 2) reduced the importance of father's occupation/parental home conditions (owner-occupier status and overcrowding) as potential predictors suggests that chronic inflammation and endothelial activation may be intermediary phenotypes in the relationship between adverse childhood home conditions and poorer lung function.

The initial multivariate model (model 1) was adjusted for age and sex.

Next, these variables were entered in a multivariate model (model 2).

First, traditional CV risk factors (age, sex, smoking, BP and BMI) were entered into the multivariate model (model 1).

Only factors identified to be significantly associated with incident retinopathy at model 2 were include in the multivariate model (model 3).

This is why our final multivariate model (model 4) may underestimate the role of material and psychosocial factors in SRH, and models 1 3 may also be informative.