We found that 25% of the variance in outcome could be attributed to between-surgeon variance.
To determine the maximum difference that could be attributed to between-measurement variability, we measured the AH interval, HA interval, and tachycardia cycle length during the typical form of AVNRT and computed Fr twice for each patient.
We also evaluated the presence of heterogeneity across trials by using the I2 statistic, which quantifies the percentage of variability that can be attributed to between-study differences [ 28].
In the current dataset it turned out that overall 19.4percentnt of the variance in euthanasia attitudes could be attributed to between-country difference; meaning the attitude toward euthanasia differed more between individual people within countries than between countries, but to a considerable extent a person's euthanasia attitude is influenced by the country he or she lives in.
We used the I statistic to assess the proportion of total variation in effect estimates that was attributed to between-city heterogeneity (Higgins and Thompson 2002).
The ICC reflects the proportion of total variance that is attributed to between-provider differences and is used as a general measure of discriminatory power.
FST captures the fraction out of the variation in allele frequencies that is attributed to between-population variation rather than within-population diversity.
The ICCs of empty models for individual diseases were between 0.0007 (stroke) and 0.008 (diabetes)—that is, 0.07 0.8% of the variance in health outcomes is attributed to between-community differences.
At two hierarchical levels, AMOVA revealed that an average of 16.5% of the genetic variation was attributed to between population diversity and 83.5% was attributed to within population diversity (Table S4).
Heterogeneity was explored using the I statistics, a measure of how much variance between studies can be attributed to differences between studies rather than chance.
