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We used the I statistic to measure the proportion of statistical heterogeneity for each outcome.
The I2 describes the proportion of statistical variability between studies in a meta-analysis that is greater than would be expected due to chance.
Because we may observe some disagreement between the direct and indirect estimates purely by chance, we used the proportion of statistical inconsistencies as the main outcome in this study.
The proportion of statistical inconsistency was higher in cases that did not do indirect comparisons than in those with explicit indirect comparisons (21% v 8%), although the difference was not statistically significant (P=0.45).
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In addition, we explored influence of various 'case and control' proportions on statistical power of the 'case and control' design for detecting LD.
There are at least two plausible complementary explanations for the result that variation in study design explained a large proportion of this statistical heterogeneity.
The Fisher exact test was used to test the difference of proportions for statistical significance.
The diagnostic performances of different modalities were compared by means of the Fisher exact test for proportions with level of statistical significance set at 0.05.
The observed proportions of the ≤ 5-degree differences were tested against proportion of 0.95 for statistical significance by one sample binomial tests.
Although the distributions of insertion sizes appear somewhat different, with the A. lyrata distribution having a longer tail of large insertions and A. thaliana having a higher proportion of small insertions, statistical tests comparing the distributions of the samples were not significant (Kolmogorov-Smirnov; p = 0.13).
Further spatial and temporal constraints on crop arrangement can be applied through separation distances, yearly proportions, and the application of statistical tests.
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