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Secondly, we produced unbiased estimators of the effects of albumin administration on mortality rates by using a propensity analysis.
These differences, however, were accounted for by using a propensity score for the evaluation of LM predictive markers (see below).
Fifth, there could be unknown bias, although we controlled for known bias by using a propensity score.
Therefore, we estimated the probability of vaccination as a function of those variables and used that score as a single matching covariate by using a propensity score analysis.
A study conducted using pharmacy claims data from 14 plans distributed over the US tried to avoid this by using a propensity score.
Thus, we aimed to investigate the association between IVF and the incidence of preeclampsia by using a propensity score matching model.
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The results of the analysis, obtained by using a propensity-score-matching model and various economic performance measures, support that indeed a "coordination premium" exists for farms that directly sell their product to the downstream agents.
We attempted to minimize confounding by using a robust propensity-matching algorithm based on potential confounders at the hospital and patient level.
Each bisphosphonate user was matched with a nonuser with the closest propensity score by using a greedy matching algorithm.
Propensity scores are estimated by using a large number of measured pretreatment covariates in a multivariate logistic regression model to predict exposure.
In other words, by using propensity scores, a collection of covariates is replaced by a single covariate, being a function of the original ones, while minimizing the loss of degrees of freedom.
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