As a secondary analysis, we analyzed the independent effect of the peritoneoscopic versus open placement technique using Cox proportional hazard modeling after adjusting for demographics and comorbidities.
Comparison between specific groups using the above regression modeling after adjusting for total tau and their associated p-values are listed in Figure 1.
In multiple regression modeling, after adjusting for other factors related to BHg, both race/ethnicity and income remained statistically significant predictors of BHg levels observed in this study [Supplemental Material, Table 11 (http://www.ehponline.org/members/2008/11674/suppl.pdf)].
Multivariate Cox modeling, after adjusting for stage at diagnosis and prior treatment history found that every one unit increase in phase angle score was associated with a relative risk of 0.82 (95% CI: 0.68 to 0.99, P = 0.041).
SHRs were attenuated in the multivariable adjusted model after adjusting for conventional risk factors for diabetes and psychological stress, but a significantly higher risk was still observed in unskilled and semiskilled workers (SHR 1.39; 95% CI 1.08 1.78).
The odds ratio (OR) and 95% confidence interval (CI) was calculated in unadjusted and multivariate-adjusted models after adjusting for age, income status, education status, marital status, job status, drinking status, hypertension, diabetes mellitus, cerebrovascular disease (CVD), BMI, and physical activity.
In order to evaluate the trends of screening pattern in each independent variable which were statistically significant in multivariable logistic analysis, the adjusted mean was calculated on the basis of the linear regression model after adjusting for other independent variables.
The only sociodemographic factor that was significant was marital status, but it did not enter into the final model after adjusting for other significant correlates.
In logistic regression models after adjusting for confounding variables (e.g., age, initial electrocardiographic rhythm, and initiation of basic life support), hospital admission and discharge rates did not differ significantly.
Logistic analysis revealed that the rs116806486 polymorphism remained associated with LOAD in a dominant model, whereas the rs6691117 polymorphism was associated with LOAD in additive and recessive models but not in a dominant model after adjusting for sex, age at onset, and APOE ε4 status.
In multivariable logistic regression analysis, the relationship between migraine and EDS was weaker than in bivariate analysis, while the pattern of increasing OR for EDS with increasing headache frequency persisted in models after adjusting for age, BMI, depression, and gender (Table 4).
