Sentence examples for minimising misclassification of from inspiring English sources

Thus, our study was uniquely able to account for the effect of changes in PPI use and the substantial increase in PPI use over the past decade on risk of fracture, minimising misclassification of exposure.

In addition, men in the intervention arm of the trial were uniformly screened for prostate cancer, therefore minimising misclassification of the outcome.

Those aged under 25 years were excluded to minimise misclassification of education level.

Moreover, we conducted an additional analysis restricting follow-up until 31 December 1996, which minimised misclassification of exposure.

We therefore grouped IBD patients with mixed codes separately to minimise misclassification of the Crohn's and ulcerative colitis groups.

10 19 WHO group 3 definition was based on Study Scientific Committee consensus applying a conservative interpretation of the literature to minimise misclassification of patients with evident lung disease as PAH.

This was done to minimise misclassification of use among people who received but did not fill the prescription or take the drug.

Although our report does not contain information on histological diagnosis, the definition of bladder cancer patients as those requiring relatively aggressive treatment should have minimised misclassification of non-cases as cases.

To minimise misclassification of cause of death, possible prostate cancer deaths are reviewed by an independent international cause of death committee blinded to the trial arms, with an embedded quality assurance process to ensure the reliability of the vignettes and the decisions of the reviewers (data to be presented separately).

This definition was found to minimise misclassifications of patients and was recommended for use to allow for comparison of programs [ 26].

However, the inclusion of patients at the large general hospital that is well-equipped with medical care facilities, an electronic medical record system, and highly precise mortality data could be the strengths of this study, minimising misclassification bias.