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Propensity score matching was used to balance the cohorts of patients prescribed saxagliptin and sitagliptin.
Propensity score matching was used to balance the cohorts of patients prescribed saxagliptin or sitagliptin.
In both, the history matching was used to obtain a reduced model parameter space.
The method based on template matching was used to successfully identify sperm cells [17] and other suspended cells [18].
Due to selection bias, propensity score matching was used to reduce confounding from differences in the patients' baseline characteristics.
A time-domain spectral matching was used to develop acceleration time histories compatible with each uniform hazard response spectrum.
Propensity score matching was used to compare trajectories of personality trait change in individuals with and without therapy experiences.
Propensity score matching was used to estimate the effects of SBHCs on indicators of adolescent utilization of health services and risky behaviors.
For base placement Triangle Matching was used and the program generated maximally 200 solutions per iteration and 200 per fragmentation.
Propensity score matching was used to minimise confounding by indication.
Predictive mean matching was used to create multiple imputations.
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