Sentence examples for average propensity score from inspiring English sources

The propensity score caliper will be set at the value that represents 0.6 standard deviations (of the average propensity score).

We then used the average propensity score to assign patients into one of the five strata.

Average propensity score =.29; SD =.36; Range =.002 -.999 # pscore statistics indicate that there is no statistical difference between A and B within each stratum (p >.05), meaning that propensity scores balanced at 6 strata Figure 2 presents the simple bar graph comparing the results of the analysis between unadjusted and adjusted by PSM.

Kaplan and Chen (2014) also assessed the predictive performance of both Bayesian model averaging propensity score approaches and compare it to the case without Bayesian model averaging.

Overall, their results showed that both Bayesian model averaging propensity score approaches recovered the treatment effect estimates well and generally provide larger uncertainty estimates, as expected.

Kaplan and Chen (2014) approximated Bayesian model averaging approach based on the model-averaged propensity score estimates produced by the R package BMA, but which ignored uncertainty in the propensity score itself.

The average antigenic propensity score of the protein was 1.019, with a maximum of 1.197 and a minimum of 0.884.

In a recent paper Kaplan and Chen (2014), investigated the use of Bayesian model averaging in propensity score analysis in a simulation study and a case study again using data from ECLS-K.

Consequently, the matrix was used to calculate each protein structure's ConQuass score, which was the average of the propensity scores of the protein's residues.

The same result is also found estimating the gender average treatment effect by weighting on the propensity score.

Both Bayesian model averaging approaches offered slightly better prediction of the propensity score compared to the Bayesian approach with a single propensity score equation.