Sentence examples for measurement error even from inspiring English sources
Our data demonstrate that in individual children, changes in diastolic wall thickness or LVMI as a result of ESRD which are expected over a period of a year cannot be distinguished from measurement error, even when measured by the same observer.
The class of IRT models is flexible enough that it should be considered as a direct model for measurement error even in cases in which number-correct score might be used, even if the test was not constructed using IRT techniques.
From a learning and teaching perspective it is problematic calling context specificity a "measurement error" even though this may be correct from a psychometric point of view.
We conclude that real-time QPCR is inherently prone to measurement error, even under conditions that would seem favorable for association studies.
Therefore, it would be important to try to decrease the measurement error even further if C7-T8 relative phase were to be considered as an outcome for studies of thoracic spine pain.
We have shown that by incorporating repeated measures of a biomarker within a unified joint model framework, we reduce bias due to measurement error, even when only the baseline level of the biomarker is predictive of survival.
If the true factor spectra are not constant as assumed by the model, E may be significantly larger than measurement errors even after all physically meaningful factors have been extracted.
In k-Neighbor TC protocol, the recommended value of k in presence of distance measurement error is even higher than the actual value needed to achieve the strong connectivity requirement for variety of network sizes.
We have also discussed the possibility that measurement error is even more severe for immigrants than for natives, in particular if their education was received in the country of origin.
In addition, genomic selection analyses may be affected by trait measurement error because even after the majority of discordant data have been removed the allele effects in the two GWAS still showed clear differences.
However, as datasets increase in size it becomes increasingly unlikely, due to noise and measurement error that even functionally related genes will retain expression similarity over all experimental samples.
