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Cost-effectiveness was then explored through the calculation of incremental cost-effectiveness ratios (ICER), defined as the difference in mean costs divided by difference in mean effects [ 20].
Cost-effectiveness will be then explored through the calculation of incremental cost-effectiveness ratios (ICER), defined as the difference in mean costs divided by difference in mean effects.
Cost-utility is explored through the calculation of incremental cost-utility ratios (ICUR), defined as the difference in mean costs divided by difference in mean QALYs [ 55].
Based on AUCs, item difficulty was the single best predictor of false positives in DIF identification for both RZ and CrI, followed by difference in mean trait level between modes.
Predictive value of ΔPOP was estimated by: difference in mean value of ΔPOP between responders and nonresponders; correlation coefficient between pre-infusion ΔPOP and CO increase after fluids; and sensitivity, specificity and area under the ROC curve (AUC) for ΔPOP to predict a responder state.
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Data showed by difference in means [95% confidence interval] in mm.; *calculated by Unpaired t test.
The chips were therefore standardized to have a mean of 0 and a standard deviation of 1, enabling data from different chips to be combined without the risk of being influenced by differences in mean or SD.
Since the activity concentration was retained to a higher extent in the tumor tissue than in the kidneys and in the blood, the T/N ratios for the kidneys and blood were higher after priming, which is reflected by differences in mean absorbed dose.
However, even in the day 0 IGHM samples that closely approximate Gaussian distributions, there are interindividual differences in repertoire evidenced by differences in mean, SD, skewness and kurtosis (Fig. 1c).
The difference in age between genotypes in our cohort for the variant rs2014886 reached statistical significance, so it is possible that the effects we note for TSFM splicing could be driven by differences in mean age rather than genotype.
Little et al. (2010) pointed out that in epidemiological studies of cancer and ionizing radiation, statistical power is influenced much more by differences in mean dose than by the number of cases.
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