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To encourage other hospitals to implement patient questionnaires and define standards enabling the possibility of comparing data, we provided a general XML schema which describes the structure and content of the forms (see additional file 1).
There was also uncertainty in the compared data, because we had direct measurements for some of the residences, but we had none for the workplaces.
Considering the differences between the compared data sets, we calculated the coefficient of repeatability as 2 × standard deviation.
Thus as a first step to check the integrity of the data, we compared data from endothelial cells to data from neurons in order to demonstrate whether the predicted differences between these two cells types could be detected.
To further test whether our normalization scheme improves the data, we compared data from replicate spots on an array before and after normalization.
To examine the influence of diabetes and prior stroke on outcomes, we compared data on thrombolysed patients with nonthrombolysed comparators.
Then we compared data obtained using infant and adult softwares successively in the same phantoms.
Finally, we compared data from two points in time: 2000 and 2010.
We compared data from patients admitted to the ICU and those admitted to the ward.
In this analysis, we compared data from patients with AHRF secondary to trauma to the general AHRF patient population.
To this end, we compared data from a standard stop-signal task, in which stop signals required response cancellation ('stop-relevant'), to data where possible stop signals were task-irrelevant ('stop-irrelevant').
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com