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If there are unit roots in any of these hypothesis tests, check the variable in first difference form to check for two unit roots.
Double check the variable.
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Bivariate analysis was conducted primarily to check the variables which had an association with the dependent variable individually.
By checking the variable importance ranked by the model, machine could feed us back with clinical features of narcolepsy on machine scale (i.e., machine tells human how it ranks the mixed features of narcolepsy in EU-NN database).
When a query message is received, a tag checks the variable isResponsible, as shown in line 13.
Final variables were selected by checking the variable importance index (a measure of the relative importance of the variables) generated from the model diagnostics and the correlations among the variables.
We first checked the variables for multi collinearity by calculating variance inflation factor (VIF).
First, we checked the variables regarding their distribution by using the Shapiro-Wilk-test and by evaluating the skewness and kurtosis.
Check the "Read variable names from the first row of the data" box if you want the variable names to be created automatically.
Simple descriptive statistical analysis was performed to check the relevant variables; we used the rule of thumb that any variable with a prevalence below 5% or higher than 95% should be excluded from the analysis.
We have no other source to check the demographic variables, the notification of symptoms and the absence or presence of social factors.
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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