Sentence examples for estimating the propensity from inspiring English sources

The results of the bivariate probit model estimating the propensity scores are given in Table 6.

There are however two ways of incorporating sampling weights when estimating the propensity score.

Main results regarding the analysis of scarring effects are the same if no weights are included when estimating the propensity scores.

Models for estimating the propensity score equation have included parametric logit regression with chosen interaction and polynomial terms (e.g., Dehejia and Wahba 1999; Hirano and Imbens 2001a), and generalized boosting modeling (McCaffrey et al. 2004), to name a few.

The coefficients are significant in the OLS regressions, especially so in the model estimating the propensity to return, which indicates that I control for some of the differences between the migrants sampled and the actual immigrant stock.

After estimating the propensity scores, we match (without replacement) companies that report under German GAAP with companies that report under IFRS and that have the closest predicted value from Eq. (9) within a maximum distance of 0.25%.

After estimating the propensities, we could obtain complexes using the estimated propensity matrix Θ = [ θ ik ].

Generalized boosting, a non-parametric modeling technique, was used to estimate the propensity scores.

The first step in estimating the treatment effect is to estimate the propensity score.

Specifically, we first estimate a Probit model to estimate the propensity of hiring returnee managers.

After implementing the logit model for cooperative membership, we estimated the propensity scores.