Sentence examples for model averaging propensity from inspiring English sources

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.

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.

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.

A) Bayesian Model Averaging.

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

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

Universities of applied sciences have an above-average propensity to KTT activities.

Responses were aggregated to obtain the "average" propensity towards a D-a-R service.

Despite a general decline in average propensity to travel further than the norm across the landscape, severity had a larger impact on travel propensity in rural areas, which increased over time.

Open image in new window Fig. 10 Average propensity towards alternatives expressed by users on 7-level semantic scale.