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The thin, continuous sections of 3D SPACE minimise the effect of partial-volume averaging, which can be a source of diagnostic error when evaluating the ACL of the knee [3].
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Another source of error when evaluating UO monitoring, and which to our knowledge has not been assessed before, is the temporal deviation of measurements with a MU, which may further lower its precision.
The spherical nature of the retinal surface cannot be accurately assessed in two-dimensional photographs and has an inherent degree of parallax error when evaluating branching angles.
A peripheral skin temperature below 32°C with sustained and normal body temperature is associated with changes in both twitch tension and TOF ratio that may be a source of error when evaluating neuromuscular function [ 25].
Nevertheless, users must consider system errors when evaluating their results.
For simplicity, our statistical model integrates only indels and mismatches because Illumina sequencing technology, in contrast to those reporting reads in color-space, does not allow mismatches to be easily categorized as SNPs or errors when evaluating single reads.
Since the subjective MOS itself has statistical uncertainty because of the abovementioned subjective factors, it is reasonable to allow certain prediction error (e.g., less than CI95) when evaluating the prediction accuracy of an objective model.
When evaluating the proposed thermal error model, the multi-collinearity problem and computational time are both improved through the correlation grouping, and the linear model is more robust against measurement noises than the engineering judgement model, which includes variables with higher order terms.
There are several additional issues other than the type I error inflation arising from PS to consider when evaluating the appropriateness of convenience controls versus controls selected to reflect the study-base that produced the cases.
When evaluating the model performance by means of the root mean square error (RMSE), a measure of individual prediction errors (Table 3 ), the above conclusions were largely confirmed: the steady-state methods (Methods 1 and 2) provided the largest RMSE with overall larger errors of predictions based on FPG than those based on MPG.
First, when evaluating the significance of correlations in Table 3, we did not take possible inflation of the familywise error into account.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com