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Using this model, we corrected a longstanding error in the literature and investigated the role of stellar spin in tidal disruption events.
In a General Linear Model we corrected for rurality and type of practice.
Applying this model we corrected all other parameters for PMA at MRI and HC.
For the multivariate model, we corrected the genome-wide suggestive and significant cut-offs as 1.52 × 10−4 and 7.59 × 10−6 through multiplying the raw thresholds by the number of phenotypes [ 29].
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As explained in the main text, in our TDB model we correct the tree distances d mr (d mr = 1 - ρ mr) for heterogeneity in the degrees of metabolites.
In order to mitigate the effects of inflated alpha due to performing multiple statistical models, we corrected the alpha for the full model using the Bonferroni method.
The apparent use of various definitions made individual comparison less reliable and by grouping the comparable models we corrected for interpretation differences.
In such models, we corrected the standard errors by taking into account repeated surveys for a particular country as a cluster.
For our artificial lattice models, we corrected for this source of error by masking each set of generated points with an experimentally obtained craniotomy outline.
In all models, we corrected for sexual risk factors, that is, number of years sexually active, number of sexual partners in the past 6 months, condom use combined with type of sexual partner (i.e., steady and/or casual partner(s)) in the past 6 months, all at follow-up.
Indeed, analysis of the annotated S. purpuratus DIA1L gene did reveal a splicing error in the gene model, which we corrected (Table S8 and Figure S10).
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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