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Discrete and continuous variables were compared between various groups using Pearson's χ2 test and unpaired t-test as appropriate.
Tree showing the relationships found between various groups using core domains.
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Phylogeny and taxonomic analysis of ELKs A) Full tree showing the relationships found between various ELK groups using core domains.
Investigation of differences in OS and DFS between various groups was performed using the log-rank test and the Fishers Exact test.
The statistical significance of difference in HEV prevalence rates between various groups was tested using the t test for continuous variables and the χ test and Fisher's exact test for categorical data.
Statistical differences between various groups were detected using either Chi-squared or adjusted Chi-squared test, Chi-squared for trend test, and non-parametric (Kruskal-Wallis) test as appropriate.
With respect to the differences in outcomes between various groups, categorical variables were compared using chi-square analysis.
To determine whether there was a significant difference between various groups, Student t test was used and statistical significance was established at P <.05.
The physiological data was analyzed for differences between the various treatment groups using Student t-tests, and One Way ANOVAs.
Principal component analysis (PCA), a tool for visualizing a multivariate response, was performed on the entire gene chip and is used to illustrate differences between various groups.
ANOVA and chi-square tests were used to compare the differences between various groups.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com