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Additionally, this test aims for variable levels of X-inactivation or other contributing factors by simply comparing variances between heterozygous and homozygous females.
Taking into account the difficulty in comparing variances between individual and area level in multilevel regression, VPC, MOR and PCV were applied to the evaluation of variance at different levels.
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By comparing variance between monozygotic and dizygotic twins it was estimated that 60% of these differences are caused by genetic factors.
F-test was used to compare variances between groups.
Shapiro Wilk normality tests were used to determine whether diameter measurements were normally distributed, and F-tests to compare variances between data pairs.
All groups of quantitative variables were checked for normal distribution by the Kolmogorov-Smirnov test, and the F test was used to compare variances between the groups.
To explore whether data acquisition differences affected findings, we compared variances between both groups using a homogeneity of variance test and found that the variances were not significantly different.
The Mann–Whitney U test (with Bonferroni's correction) was used to compare variance between groups.
Analysis of variance of the RILs was used to quantify and compare variance between and within RILs.
The one-way ANOVA and Bonferroni or Tamhane's T2 methods were used to compare variance between groups.
CV is the unitless ratio of the standard deviation to the mean, and is commonly used to compare variance between independent variables that may differ in scale and averages.
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