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To ensure that CPU (with double flash separators) can be operated under optimal conditions, this paper focuses on single variable analysis, multi-variable optimization, dynamic simulation and control system design for CPU in oxy-combustion power plants.
We conducted a single variable analysis wherein each risk factor was examined for its association with severe CDAD.
Results from the single variable analysis are shown in Table 4 and ribotype 027, sex, discharge from hospital within 60 days of current admission, gastroenteritis on admission, number of initiator antibiotics for CDAD, and hospital where the patient was admitted were included in the model.
A single variable analysis was performed.
This was indicated in the single variable analysis, as low values of Barthel and Katz Indexes.
Single variable analysis between two samples was compared by Student's t-test.
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Because only single-variable analysis could be performed, we could not assess the extent to which concurrent conditions were correlated, which led to the potential for uncontrolled confounding.
Combining clinico-pathological variables that are proven to be associated with clinical outcomes allows more accurate prediction than single-variable analysis.
We then investigated subtypes for relationships with reported exposures by using single-variable analysis performed in SPSS 12.0 version (SPSS Inc., Chicago, IL, USA).
A p value ≤0.15 was used in the single-variable analysis to select variables for the multivariable model built in backward stepwise fashion.
The correlation-based networks have enabled us to detect novel relationships between disease-related phenotypes that would not have been observed in a single-variable analysis.
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