Your English writing platform
Discover LudwigExact(6)
In the first model including each single criteria of MetS (SBP, DBP, waist, fasting glucose, HDL cholesterol and tryglicerides along with diagnosis of diabetes or dyslipidemia), only SBP resulted independently associated with LVH/h2.7 (table 3, model 1).
We used the cNRI-driven forward variable selection (see STATISTICAL METHODS for details) to build the 2-year mortality risk prediction model, including each predictor one by one.
To determine the effect of RBC age on in-hospital and long-term clinical outcomes, we constructed each adjusted model including each RBC age as a covariate after forward variable selection although they showed insignificant results in the univariate analysis.
The final effect was that the sum of model-specific estimates of discontinuation from all states in the model, including each type of adverse event, matches the annual CATIE phase 1 discontinuation rates for any cause.
Changes in height-, weight- and BMI-SDS across time from diagnosis were explored using a univariate model including each of these as the dependent variable, incorporating both the time from diagnosis and subject identification.
To further assess the combined effects of both markers, we generated an equation, combined risk score = exp [ 0.054 x log square transformed values of lipocalin-2) + (0.024 x log square transformed values of MMP-9 ] MMP-9 ]on the linear regression model using the coefficients of each marker determined basede multivariate monel including each marker (contheuous) and adjustment variablinear
Similar(54)
The first multivariate model included each determinant and country of recruitment.
The fitted model included each one of two tested factors as first-order components and an interaction term reflecting the extent of the allelic by allelic epistasis.
The single SNP regression (SSR) model included each SNP separately as a continuous variable (i.e., count of a given allele) in a linear animal mixed model using ASReml [ 15].
We analyzed data from 3917 allogeneic HCT recipients at multiple sites in the United States and Italy using multivariate models including each biomarker and the HCT-CI.
We used multivariable logistic regression to build our predictive models including each variable category in an incremental fashion.
Write better and faster with AI suggestions while staying true to your unique style.
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