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The normality of distributions of the variables was tested with the Kolmogorov-Smirnov test with Lilliefors significance correction.
The data was examined to determine if it came from a normal distribution using either the Kolmogorov-Smirnov test with Lilliefors significance correction or the Shapiro-Wilk test, depending on the degrees of freedom.
Homogeneity of variances was calculated using Levene's test and Lilliefors significance correction.
Data were tested for normality using the Kolmogorov-Smirnov with Lilliefors significance correction and data are reported accordingly.
Normality of each of the items on the FRAS was assessed using the Kolmogorov-Smirnov test with a Lilliefors significance correction and the Shapiro-Wilk test of normality.
QQ-plots, box plots, a ratio analysis and Kolmogorov-Smirnov (with Lilliefors significance correction) as well as Shapiro-Wilk tests were performed to evaluate normal distribution of the data.
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Section 'Methods: Significance level correction' presents the different methods of correction of the Type-I error.
Comparing CR polymorphisms of cancer patients to controls we found two out of 219 statistically significant differences, which lost their significance after correction for multiple comparisons.
For males, this relationship was initially significant for ICD-9 but did not surpass significance upon correction (p=0.030, χ=4.688).
However, this difference was borderline significance after correction for multiple comparisons.
Age was the most prominent factor in reducing significance after correction.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com