The JMP software allows to evaluate the linear correlation coefficient between the couple of variables identified.
Variables identified to be present in fewer than ten patients were also removed (i.e., near drowning, thoracic surgery).
Step 2: From the variables identified in step 1, the contextual relationships among the variables are found.
A broadscale clustering of the nearshore variables identified three general regions distinguished primarily by temperature, plankton, and specific conductivity.
Main Outcome Measures: Demographic and clinical data, including variables identified previously as predictive of weaning success among highly selected populations.
Key influential variables identified by follow-up sensitivity analyses were related with topographic dimension, environmental heterogeneity, and water column properties.
The influential variables identified included the outside and inside shoulder widths, median width, lane width, traffic volume, and shoulder type.
Only 2 studies attempted to prospectively validate a predictive model for RBC transfusion based on the variables identified.
Odds ratios (OR) and 95% confidence intervals (CI) adjusted for variables identified in univariate analyses were calculated using logistic regression.
The second was additionally adjusted for variables identified as being associated with both CRC and energy balance from previous literature.
No study reported the full set of all donor variable and recipient variables identified as being of possible importance.
