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Variables considered for inclusion in the models were assessed for missing data.
Variables tested for inclusion in the models included HIV status, age, serum albumin, BMI, lean body mass, total body fat, and systolic and diastolic blood pressure.
When two or more explanatory variables were correlated we selected the variable that was most significantly related to the response variable [55] for inclusion in the models.
No interactions between characteristics were considered for inclusion in the models.
All variables with <20% missing data were assessed for inclusion in the models.
Variables with P < 0.10 in bivariate analysis were considered for inclusion in the models.
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AQS monitors within the modeling regions were considered for inclusion in the model, and predictions at participant residences were restricted to locations within these modeling regions.
For regression models, covariates for inclusion in the model were identified from bivariate analyses.
To improve the results, we develop a parameterization of the lubrication forces for inclusion in the model.
A multiple stepwise logistic regression model was established with any covariate with univariate significance of P value <0.10 eligible for inclusion in the model.
Stepwise logistic regression was subsequently led to analyze risk factors for VAP treatment failure, with a threshold of p < 0.1 for inclusion in the model.
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