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Many of Riesz's fundamental findings in functional analysis were incorporated with those of Stefan Banach of Poland.
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Variables with a p-value < 0.20 in the bivariate analysis were incorporated into the multivariate models and those with p-value < 0.05 remained in the final model.
Variables with p < 0.1 in bivariate analysis were incorporated into Logistic regression model for risk adjustment.
All predictors showing a P < 0.1 association with ICU-acquired infection in univariate analysis were incorporated in the multivariate logistic regression analysis.
All variables with a p value <0.20 in the univariate analysis were incorporated into the model.
Factors with a P value < 0.2 in the univariate analysis were incorporated into the multivariate analysis.
Independent variables with a p-value < 0.20 in the unadjusted analysis were incorporated into the adjusted regression model.
Explanatory variables with a p-value < 0.20 in the bivariate analysis were incorporated into the multivariate model.
The analysis outcomes were incorporated with the Saudi energy sector requirements and local weather conditions to define alternative scenarios.
We demonstrate that when the "risk genotypes" derived from the univariate analysis are incorporated into an algorithm with clinical variables, independently associated with lung cancer in multivariate analysis, modest discrimination is possible on receiver operator curve analysis (AUC = 0.70).
Briefly, any variable with a P-value of < 0.2 in univariate analysis was incorporated in multivariate models, wherein only variables with a P-value of ≤ 0.1 were retained.
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