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Two multivariable analysis models were examined.
Variables found to be significant at the p < 0.10 were included in the final multivariable analysis models.
In the multivariable analysis models, a manual stepwise backwards elimination process was used to identify factors that were significantly associated with the study outcomes using 5% significance level.
In the multivariable analysis models, we adjusted these confounders to investigate the individual effect of VAP on medical expenses and utilization.
In the multivariable analysis models, a manual procedure of stepwise backward elimination process was used to identify factors that were significantly associated with the study outcomes using 5%% significance level.
Similar(55)
These two factors remained significant after adjustment for confounding by age and sex in the multivariable analysis model.
A multivariable analysis model is presented for secondary outcome.
We selected age as the covariate in multivariable analysis model 1.
This article attempts to inform the debate by a multivariable analysis model.
The first multivariable analysis model included baseline glycemia measures to examine whether they related to the chosen outcome measures (model 1).
The TIMP-1 remained prognostic for survival in a multivariable analysis model that included performance status, risk group and other biomarkers.
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