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The variability in the selection criteria for RCTs and sample size, along with the incomplete reporting of intervention intensity, may also be limitations.
The large variability in the selection of imaging acquisition parameters in MRI provides a considerable challenge in connecting data from multiple imaging biobanks worldwide.
Particular anatomic landmarks pose challenges due to variation in morphology and convexity, such as condylion, gonion, and porion and there can be a greater degree of variability in the selection as shown by intra- and interrater reliability measures [33, 34].
There is some scatter in the data, perhaps reflecting the inherent variability in the selection response and the possible existence of multiple resistance mechanisms.
Our review of VA studies published up to 2012 highlights variability in the selection, development, and use of VA instruments, as well as in methods of assessment.
We assumed that variability in the selection of mutations due to the restricted sample size might essentially play a role in the first selection step.
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However, the reports have great variability in the patient selection, prior treatments, the choice of the conditioning regimen and variability of the doses within the same regimen.
For many observational data analyses, the variability in the treatment selection process within clinical centers is ignored.
Furthermore, there is no consensus on the best approach for dealing with variability in the treatment selection process across clinical centers.
The application involves great variability in the instrument selection factors.
The NF1-CTD protocol provides a rich illustration because it encompasses great variability in the instrument selection factors, and these patients with their supportive caregivers face numerous complex health status challenges with long-term implications for HRQL.
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