Using logistic regression, propensity groups were derived based on the predicted probability of cohort membership.
The propensity for group events to lead to future group events was variable (Table 7).
A propensity score matched group was used as control subjects.
To check consistencies among predictors of the same physico-chemical propensity, we group the properties by higher level features and also highlight the ones that pass the selection criteria (Fig. 2 and Supplementary Fig. S1).
To test whether there is any relationship between the theoretical pI of a protein and its predicted deposition propensity, we grouped the polypeptides in the cytosolic fraction according to their pIs.
Under propensity matched groups, patients were matched by their probability to receive a transfusion, thus statistically reducing confounding bias.
Table 2 shows the baseline characteristics of the unmatched and propensity score matched groups without mechanical ventilation.
Table 1 shows the baseline characteristics of the unmatched and propensity score matched groups among mechanically ventilated patients.
We applied singlet and doublet propensities of group G-2 to the whole cDNAs (open reading frames) for the rps4 psbE and clpP rpoA sequences (Fig. 1).
In addition, with small sample sizes and a relatively large number of propensity score groups, application of the ABB method is problematic, especially for binary variables.
