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The algorithm strategically uses both unweighted and weighted statistical testing in a multiple-decision framework.
The panel determined that only half of the abilities could be tested in a multiple choice format, the judge wrote, and two abilities that the panel ranked as most important — oral comprehension and oral expression — were omitted because it was not feasible to conduct interviews with thousands of applicants.
Variables found significant (p<0.05) by univariate logistic regression were tested in a multiple variable model to determine risk-adjusted association with mortality.
The association between genotype and MEQ or PSQI scores was tested in a multiple, linear regression model, adjusted for age, gender and shift work.
Instead all variables were tested univariately, and only significant values were tested in a multiple regression model.
Potential interactions were tested in a multiple regression model.
Subsequently, they were also tested in a multiple regression model.
* Student t test on log transformed data These findings were tested in a multiple regression model.
Assumed predictors of overtriage and undertriage were tested in a multiple logistic regression analysis.
The association between NDRS and log-transformed values of FENO was tested in a multiple linear regression model.
Usually, the number of tests in a multiple comparison test is up to about 20, or possibly 100 in an extreme case.
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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