Third, the multivariable analysis considers only variables included in the statistical model, and the influence of unmeasured variables cannot be accounted for.
The linear predictor resulting from the multivariable analysis considering the 5-serological cancer biomarkers – bilirubin, albumin, AFP-L3, AFP, and DCP – as potential prognostic factors is reported below.
Fifthly, although in the multivariable analysis we considered a multitude of lifestyle and dietary factors, including other individual fruits, residual or unmeasured confounding may still exist.
First, although in the multivariable analysis we considered a multitude of lifestyle and dietary factors, the possibility of residual confounding or confounding by unmeasured factors, which cannot be ruled out in any observational study, must be acknowledged.
Among the variables with a P value < 0.20 in univariate analysis, we selected covariates in multivariable logistic regression analysis considering known risk factors or relationships to hemodynamics during surgery to determine independent risk factors for AKI.
To find out correlates of traditional cooking energy utilization, bivariate and multivariable analysis were conducted considering sociodemographic variables, knowledge related variables, fuel related variables, and sociocultural variables as independent variables and traditional cooking energy utilization as dependent variable.
When the multivariable analysis was repeated considering each ACHD complexity subgroup separately, albumin was a significant independent predictor of death in patients with moderate or great ACHD complexity, while a trend was present for simple ACHD (p=0.063).
In a multivariable analysis of controls that considered the same potential predictors as above except migraine frequency, only age and sex were significant independent predictors.
In a multivariable analysis of migraineurs that considered sex, number of medications used, migraine frequency (days) in the past year, psychiatric measures, and number of comorbidities as potential predictors of PC-PLC activity, only number of comorbidities was independently significantly related to PC-PLC (parameter estimate (SE) = 1.77 (0.58), p = 0.009; Table 3).
In the multivariable analysis, three variables were considered clinically important: age, education and group.
