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Results are reported as percent reductions and significance is based on t-tests and ANOVA models of log reductions.
All association p values are from linear models of log(BMI).
To estimate the average annual reduction in under-five mortality across the 213 districts retained in the analysis, we fitted various random effects models of log (under-five death rate) against year to the data from these districts.
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Section 2 provides a review on statistical models of log-logistic, log-normal, Weibull, and Nakagami, and discusses their applicability for foliage clutter modeling.
Multivariate analyses were performed using generalized linear models of log-transformed costs.
Exponentiated regression coefficients from models of log-transformed serum PBDE concentrations represent the percent change in the geometric mean (GM) concentration associated with exposure.
We computed geometric mean phthalate metabolite concentrations within diagnosis groups, testing differences by case status using linear regression models of log-transformed phthalate concentrations.
In regression models of log-transformed MEHP, the regression parameters estimated MEHP levels in the medium- and high-DEHP exposure groups as a proportion of MEHP levels in the low-DEHP exposure group.
For some continuous individual TLR variables log-transformation produced significant improvements in model fit and, for consistency, all significance results, unless otherwise indicated, relate to models of log-transformed TNF-α (pg/ml).
Ulcerative colitis showed a significant positive association with cumulative PFOA exposure, with monotonically increasing rate ratios for both the unlagged and lagged exposures and significant trends based on models of log-transformed cumulative exposure.
The linear regression coefficients for floor wipe concentrations ranged from 0.03 to 0.15 for BDE-47, 99, and 100 in mixed effect models of log-transformed serum concentrations, which means for every 1 pg/cm increase of the floor wipe concentration, the geometric mean serum concentration would increase by a factor ranging from 1.03 to 1.16.
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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