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Both associations were confirmed by multiple logistic regressions.
Multiple logistic regressions were applied to relate the use of sunscreen and skin cancer awareness with various socio-demographic variables.
Multiple logistic regressions were adjusted for socio-demographic characteristics, clinical variables, and for 4 other frailty components.
Univariable and multiple logistic regressions were applied to assess the potential risk factors associated with the occurrence of this disease.
Multiple logistic regressions were used separately to evaluate independent predictors of smartphone app usage and preference.
Forward stepwise selection was applied and consistently significant clinical measures were analyzed for their association with individual dimensions of EQ-5D in multiple logistic regressions.
The results of multiple logistic regressions of variables relating to 28-day mortality are given in Table 2.
Multivariate analysis was conducted using multiple logistic regressions.
Multiple logistic regressions adjusted for clustering will be explored.
Multiple logistic regressions of factors associated with poor outcome.
Multiple logistic regressions were employed to identify potential predictors.
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