Ideally, additional variables such as age and race could have been included in a multivariable model examining false-positive results by pregnancy status.
Figure 2 depicts the results of a multivariable model examining the association of the Framingham risk and coronary calcium scores after adjusting for disease status, age, gender, and homocysteine.
In a multivariable model examining demographic factors related to missing eGFR, black race (OR = 1.73, 95% CI 1.48-2.01) and gender (OR = 1.18, 95% CI 1.01-1.38) were both positively associated with missing eGFR.
Multivariable models examined diabetes prevalence by race/ethnicity and birth country.
Linear multivariable models examined the joint effect of rhinitis and OSA parameters with control for potential confounders.
Multivariable modelling examined the independent contributions of the risk factors that met criteria for meaningful association with activity-limiting MSDs in the bivariate analyses, see Table 4.
Multivariable models examining the association between AIAA and TTTA7 and TTTA8 genotypes were adjusted for time since LMP, reason for menopause, time since start of AI therapy, education level, and chemotherapy.
There were significant crude associations between %FGV and months of breast-feeding, parity, age at first birth, birthweight, and PIH.> Table 3 presents the results of multivariable models examining the effect of first birth characteristics on breast density overall and stratified by age at first birth.
The three multivariable models examining the relative effects of prescription opioid injection and heroin injection all were adjusted for gender and age, as well as for variables significant at p<0.05 in unadjusted Cox regression analyses (cocaine injection, crystal methamphetamine injection and syringe sharing).
Using another multivariable model, we examined the association between respondents' taking antibiotics in the prior 4 weeks and their attitudes toward and knowledge of the adverse effects of antibiotic use (Table 4).
