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All adjusted proportions and Cox-regression models were controlled for propensity score as well as several additional prespecified covariates.
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Despite these limitations, the coefficient for ultrasound receipt was still significantly different from zero (P = 0.032) when controlling for propensity score quartile.> -wrap-foot> Logistic regression analysis of propensity score quartiles and use of real-time ultrasound guidance as predictors of any complications of tracheostomy.
Assessments were conducted and measured uniformly between treatment groups, and through control of the baseline HRQoL covariates and use of the random-effects model, the analysis incorporated and controlled for the propensity to respond in a certain way.
To improve comparability of the 2 vaccine groups, we controlled for the propensity score in multivariate models, but first we excluded all outlier observations ("trimming"), defined as those below the lower 2.5% of the tail of the TIV observations (3,355 observations) and above the upper 2.5% tail of the ATIV observations (2,894 observations).
We predicted that female body size, statistically controlled in the model for male body size, would show a negative relationship with female bridging propensity, which was statistically controlled for male bridging propensity by including this variable on the right hand side of the model.
The trend may be due to the early mortality benefit seen with thoracoscopic lobectomy or selection biases (unknown confounders) that cannot be controlled for in our propensity matching.
These analyses will also control for the propensity to receive an initial prescription.
We will test for differences in rates using fixed effects conditional Poisson regression models, controlling for the propensity score and residual imbalances among important covariates.
We assessed ad exposure to non-tobacco products to control for the propensity to be receptive or attentive to advertising in general, which could confound the relation between tobacco-specific advertising exposure and smoking behaviour.
To control confounding, we first assembled cohorts by matching and then controlled for remaining imbalances by using propensity scores weighting.
In order to achieve an unbiased comparison of costs, we controlled for recruitment bias using the propensity score method [ 20, 21].
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