Sentence examples for propensity model from inspiring English sources

Beyond the theoretical support, we show empirically that the proposed learning method is highly effective in dealing with biases, that it is robust to noise and propensity model misspecification, and that it scales efficiently.

A complete set of baseline data is essential to develop a propensity model.

Treatment with induction chemoradiation therapy prior to surgical resection is associated with significant improvement in long-term survival, even after adjusting for confounders with a propensity model.

Propensity modeling refers to the use of machine-based learning algorithms to process copious amounts of historical data, enabling the creation of a propensity model that can make accurate predictions on things like contact information and lead elements.

After creating a propensity model and adjusting for variables predictive of mortality in the multivariable analysis, beta blocker therapy continued to be associated with a significant reduction in mortality.

As revealed by the propensity model, induction therapy was associated with higher rates of negative margins and shorter hospital length of stay, but no differences in unplanned readmission and 30-day mortality rates.

Progression rates in a propensity score matched cohort were compared between statin users and nonusers using McNemar's test with the propensity model derived using associated medical and demographic factors.

Adjusting for potential confounders was performed using a propensity model.

We addressed this issue through adjustment using a propensity model.

Propensity model parameter estimates and estimated OR. Table S2.

Model development was broken into two phases: propensity model development and mortality model development.