Because of the linear dependence of the third propensity score on the other two, only the first two propensity scores were included in subsequent analyses of the effect of the confidant social network upon use of residential care.
The second Cox proportional hazard model assessed the association between switching from vancomycin to nafcillin or cefazolin versus remaining on vancomycin and mortality controlling for the second propensity score.
In the second propensity score analysis, we matched patients exposed to proton pump inhibitors to those exposed to H2 receptor antagonists in a fixed 1 1 ratio by using a nearest neighbor algorithm with a maximum matching distance of 0.05.
In the first stage, propensity scores (predicted probability of a patient having orthognathic surgery) were computed by using covariates (age at start of treatment, gender, initial discrepancy index, initial ANB angle, initial FMIA angle, initial IMPA angle, initial U1 to SN angle, initial overbite, and initial overjet).
The first quintile (propensity score, 0 to 0.2) included 59 patients, the second (0.21 to 0.40) 848 patients, the third (0.41 to 0.60 4955 patients, the fourth (0.61 to 0.80) 259 patients, and the fifth (0.81 to 1) 2 patients.
First, propensity score matching was used to minimize the observed baseline differences between the insured and uninsured populations.
First, propensity score methods are best applicable in large data sets.
First, propensity scores, that is conditional probabilities of experiencing early unemployment, are estimated based on a set of potentially confounding variables.
Similar to the first study, propensity-score matching achieved a nearly equal distribution of available pre-operative patient characteristics between cases and controls (Table 2).
