The phrase "adjustment for propensity" is correct and usable in written English.
It can be used in contexts related to statistics, research, or analysis where adjustments are made based on the likelihood or tendency of certain outcomes.
Example: "The researchers made an adjustment for propensity to ensure that the results were not biased by pre-existing differences among the participants."
Alternatives: "correction for bias" or "modification for likelihood".
Only minimal differences in baseline characteristics remained after adjustment for propensity score, as indicated by the adjusted P values in Table 1.
Adjustment for propensity score did not alter risk of mortality (adjusted HR 0.82; 95% CI 0.57 1.19; p 0.30).
Logistic regression analysis with adjustment for propensity score quintiles showed that the in-hospital mortality rate (adjusted OR = 0.88; 95% CI = 0.43 to 1.78; P = 0.711) and the rate of interventions for infectious complications (adjusted OR = 6.42, 95% CI = 0.75 to 54.6; P = 0.089) were similar in the matched CRAI and non-CRAI groups (Table 4).
The cohort study design could be used each season to estimate VE; however, residual confounding by indication could still present issues, despite adjustment for propensity to consult.
Adjustment for propensity score performs better in these circumstances.
This does not surprise us, as adjustment for propensity scores also did not change our results.
After adjustments for propensity score, insulin and use of medication potentially associated with acute pancreatitis, the odds ratio with exenatide twice daily exposure was 0.95 (95%CI 0.65 1.38).
Further adjustment for the propensity score did not significantly alter this result (adjusted odds ratio (OR) = 1.40, 95% confidence interval (CI) = 0.74 to 2.65).
After adjustment for the propensity scores and patient level covariates, those treated surgically had significantly lower deband ANB angle and higher upper incisor to SN plane angle compared to those treated non-surgically.
Adjustment for the propensity score did not modify hazard ratio estimates for lipid lowering drug use (1.09 (0.87 to 1.36) for coronary event and 0.65 (0.48 to 0.88) for stroke).
First, incorporating adjustment for the propensity score into the sensitivity analysis would provide an efficient way of controlling for the effect of measured covariates (Rosenbaum, 1991).
