Sentence examples for derived propensity from inspiring English sources

During the course of this manuscript we discuss tests for determining the quality of the derived propensity score, various techniques for utilizing propensity scores, and also the potential limitations of this technique.

First, we derived propensity scores for statin therapy for each patient by using a nonparsimonious logistic regression model that included statin exposure as the dependent variable and an extensive list of variables related to either the prescription of statins or the risk of herpes zoster (Supplementary Appendix).

We attempted to control for both health status and health-seeking behavior by including a measure of chronic disease burden, a summary preventive services index, and an empirically derived propensity score in our regression models; however, it is possible that the observed differences are still subject to residual confounding.

Logistic regression was used to derive propensity scores 30 using all eligible patients from the initiators' cohorts to create a matched subgroup (exenatide BID vs insulin).

This study improved on previous methods by excluding data for 6 months after first secure email use, comprehensively adjusting for baseline utilisation, deriving propensity scores from a robust set of independent variables, and examining clinical services utilisation 7 18 months after the index date.

Logistic regression models will be used with the patient discharge data (patient demographics, co-morbidities, diagnostic categories) to derive propensity scores, based on factors affecting the likelihood of mortality and failure-to-rescue, which will serve as case mix adjusters in further analyses.

We then derived a propensity score weight: each patient was weighted with the inverse of the propensity score in the intervention group and with the inverse of one minus the propensity score in the control group.

There are other algorithms, such as PAPA and PrionW, using an experimentally derived prion propensity score combined with explicit consideration of the intrinsic disorder, that help to predict prion domains bioinformatically35,36,37,38.

We derived a propensity score for every patient from all the potential confounders prespecified in our primary analysis.

To address any indication bias, we derived a propensity score predicting the likelihood to receive albumin and matched 141 cases to 141 controls with a similar risk profile.

Weights were derived from propensity score modeling of the probability of incident rectal STI as a function of potential confounders, including UAI in the interval of rectal STI acquisition/censoring.