Sentence examples for bias in measurements of from inspiring English sources

Bland-Altman analysis indicated no obvious bias in measurements of neointimal lesions induced by either injury (Figure 3a,b) but a small positive bias in OPT-derived measurements of lesion size in the brachiocephalic artery (Figure 3c), possibly reflecting shrinkage of these larger vessels during histological processing.

Additionally, the biochemical assays were conducted in several Community Healthcare Centers, which may have led to inter-lab bias in measurements of HbA1c.

If there are systematic differences, this suggests that closing the survey too soon after the first questionnaire and/or failing to send out reminders would have led to bias in measurements of patients' experiences in hospitals in the NHS.

However, we were cautious in selecting steady-state patients by using criteria to avoid bias in measurements of water compartments and in BCM calculation, limiting the generalization of our results to other ICU populations.

Bland-Altman analysis indicates no obvious systematic bias in measurements of infarct volume (6.01% LV, n = 9), and all plots were within the limits of agreement (± 1.96 SD, −3.19 to 15.21% LV, Fig. 5 F ). Left ventricular ejection fraction (LVEF) was measured by cine-MRI at the time of LGE-MRI assessment as an index of systolic function.

Although studies were observational, they were generally of reasonable quality and did not suffer from significant bias in measurement of LTFU outcomes.

The first 90-120 min of all movies were removed from analysis to avoid bias in measurements due to adaptation of the slice in the chamber incubator.

The median value has been used in science and engineering for centuries to filter out the effects of bias in measurements.

Lower performance with WHiR can relate to the larger likelihood for random variation and/or bias in the measurements of both waist and hip, and perhaps particularly for hip (as we found in our data), compared to easier and more standardized measurements of height, weight and the related indices.

One, we acknowledge the existence of bias in measurement by clearly reporting limitations of data.

In addition, the anthropometric equation applied in the twelve elderly with BMI ≥30 led to a higher risk of bias in the measurement of skeletal muscle mass, which cannot indicate sarcopenic obesity in the elderly.