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For Chlamydomonas cpDNA, a parametric bootstrap approach was used to test if gene order evolves under selection [ 49].
A bootstrap approach was used to construct 95% confidence intervals (CI) around cohort effects and mean MMSE estimates [ 25].
Given the small size of the test dataset, a 100-fold bootstrap approach was used to obtain a reliable evaluation of the percentage of correct identification.
To verify that these ASD differences are significant, a bootstrap approach was used with the null hypothesis: H0: ASD (p 1, p 2) = ASD (p 1, p 3), where the ASD between populations p 1 and p 2 is compared with the ASD between populations p 2 and p 3 (supplementary note S2, Supplementary Material online).
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Linear regression and a non-parametric bootstrap approach were used to determine the dependence of residual beta cell mass to age at onset.
A non-parametric bootstrapping approach was used for this health economic analysis.
Finally, the sophisticated bootstrapping approach was used to test the relationship between intentional and unintentional non-adherence.
Bootstrap approaches were used to determine whether non-additive interactions exist among mutation types and if the number of de-repressions per hemisegment differed between morphologically normal and abnormal hemisegments of a given mutation type.
The bootstrap method based on the replication approach was used in this article for the variance estimation.
The same approach was used for the bootstrap support, but not for the SH support which applies only to clades that belong to the ML tree.
Three different approaches were used to account for the impact of serial correlation on the MK test, and a regional MK approach and a bootstrap resampling approach were used to account for the cross-correlation structure in the data.
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