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Although EPHB4 did not meet the variance cut-off observed in the initial set, distinct polymorphic methylation was observed with 3 of the 49 samples exhibiting a "methylated" state (Figure S3B).
To perform a robust Rasch analysis on each of these domains, we included all their candidate items, even though some did not meet the variance criterion.
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Data were rank-transformed where needed to meet the equal variance assumptions of ANOVA.
Category fluency scores did not meet the equal variance assumption and were therefore log-transformed.
As hardness data was normally distributed but did not meet the equal variance assumption, a Welch ANOVA followed by Games-Howell post-hoc testing was applied.
The natural logarithm of tail flick latency data was used for ANOVA analysis in order to meet the homogeneity of variance and normality distribution.
The natural logarithm of rearing data was used for data analysis in order to meet the homogeneity of variance and normality distribution.
Where data could not be transformed to meet the assumptions of variance structure for ANOVA, a Mann–Whitney U test was conducted.
Data transformation (natural logarithm transformation) was used for the data for rearing and tail flick latency to meet the homogeneity of variance and normality.
Dependent variables (tree phenotypes) were tested for normality and homogeneity of variance using Anderson-Darling and equal variance (Bartlett) tests to meet the assumptions of analysis of variance (ANOVA).
However, severe heterogeneity of variance in the initial linear regression models required the application of a generalised least squares extension to determine appropriate variance-covariate terms and meet the assumptions of homogeneity of variance [[42], [44], see Text S3].
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