To address potential response bias issues, we will use standard statistical methodologies and implement propensity-based and imputation methods with imputation of smoking status or treatment utilization at follow-up.
Using consumption per adult equivalent as a wellbeing indicator, we measured the impact of agricultural cooperative membership by implementing propensity score matching and endogenous switching regression estimation techniques.
As the intensity of training measure is a continuous variable, we implement generalized propensity scores (GPS) with continuous treatments (Hirano and Imbens 2004) to estimate dose response functions on wage growth.
Since finding an exact match becomes increasingly difficult as more covariates are used, we implement the propensity score matching (PSM) technique first introduced by Rosenbaum and Rubin [14] and frequently used in the program evaluation literature.
To address potential response bias issues, we will implement a propensity-based imputation methodology and pattern-mixture methods in a sensitivity analysis of the primary analyses described above.
There are four approaches that are commonly used in implementing the propensity score (a) stratification on (hat{e}(Z)), (b) propensity score weighting, (c) optimal full matching, and (d) propensity score regression.
Consequently, we implemented a propensity score matching method to reduce this bias 16 by first creating a propensity score to represent the relationship between multiple characteristics and the matching outcome: being in the prison group (treatments) or not (controls).
Still another approach to implementing the propensity score is based on weighting.
The third common approach for implementing the propensity score is based on the idea of statistical matching (see e.g. Hansen 2004; Hansen and Klopfer 2006; Rässler 2002; Rosenbaum 1989).
By implementing a propensity score matching estimator method, we show that engaging in consulting activities has an overall negative relationship with the average number of ISI-publications.
When implementing the propensity score matching for our two comparisons, we use kernel-based matching as developed in STATA package ATTK [ 17].
