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Each correlation between any two repeated measurements may be unique.
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Although no gold standard measurements of X a and X s via a validation subsample are available for this circumstance, the discrepancy between the two repeated measurements allows us to estimate the misclassification probabilities under certain assumptions.
The differences between the two repeated SUVmax readings at 60 min were all less than one in absolute terms, apart from those of patient no. 3, 5, 10, 23, 26, and 42 (Fig. 1).
The upper limit for mismatches between the two repeated segments was 10%.
Figure 6 shows similar results between the two repeated measurements, as well as the biometric changes between the two states.
To analyze the agreement between the two repeated measurements at 12-month the intraclass correlation coefficient (ICC) was applied.
The kappa coefficients for the agreement between the two repeated measurements were 0.80 and 0.75 for asthma and smoking, respectively.
Based on fold-change expression, genes that were differentially expressed between the two repeated microarray experiments were subjected to a scatter-plot analysis.
The reproducibility was evaluated by computing, for each tissue, the volume difference between the two repeated imaging sessions for both kNN and PCDA classifiers.
The measurement results are highly repeatable, with a correlation between two repeated measurements up to 0.98.
This means that the absolute difference between two repeated measurements lies between this value with a probability of 95%%.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com