Multivariate regression was used to control for potentially confounding variables.
These effects were significant after controlling for potentially confounding variables.
We performed multivariable logistic regression to assess the association between urban/rural location and mortality while controlling for potentially confounding variables.
The protective effect of the sling procedure remained highly significant (odds ratio, 0.29; P =.0003), even after controlling for potentially confounding variables in a multiple logistic regression model.
After adjustment for potentially confounding variables (age, gender, seatbelt use, seat position and vehicle curbweight), the significant relationship between occupant weight and mortality persisted.
Future studies should be designed to control for potentially confounding variables and assess the differences in range of motion after total ankle replacement.
The majority of studies reviewed contained methodological weaknesses including; inappropriate study design, limited sample representativeness, the use of ecological data to evaluate individual behaviour change and failure to adequately control for potentially confounding variables.
Finally, although we calculated crude risks, significant excess risks, especially for HSV-2, persisted in a sub-set of studies that adjusted for potentially confounding variables (Table 2).
To assess vaccine versus placebo geometric mean fold rises in serum antibody titers, after controlling for potentially confounding variables, multiple linear regression models were fitted.
Models controlled for potentially confounding variables, including baseline demographic characteristics and biological/clinical measures (listed in Table 1), and time dependent behavioral and biological measures.
Table 3 presents the results of multivariate logistic regression analyses modelling the associations between hypertensive target organ damage and selected variables of interest adjusted for potentially confounding variables.
