… The CST is a statistical method, which can be used to test the … When the dependent variable
is categorical, it can be used to … 11, we can see the distribution of variables is normal and no …

… For such datasets, logistic regression models would not be … The method is based on testing
the null hypothesis that the … In our data, we have categorical variables with the number of …

… considered the standard surgical procedure in the treatment … χ 2 test and Mann–Whitney test
for categorical and numerical … Univariate and multivariate logistic regression analyses were …

… test or Student t-test for categorical or numerical variables, respectively. Logistic regression
… -19 disease, we aimed to determine the significance of lipase levels on the clinical outcome …

… of falsely classified entries for categorical variables) between the … variables, suggesting that
subsequent significance testing … methods was weaker for logistic regression models because …

… The methods used to derive CBC parameters are based on … We compared categorical
variables and continuous variables … a weighted multivariate logistic regression analysis (Table 3), …

… a categorical covariate x i c , continuous covariates … testing, and validation sets of equal
size n = 500. We set 1 ( x c = C ) as the covariate of interest in the subsequent logistic regression …

… make the currently applied diagnosis methods are still not very ideal … Chi-square test were
used for categorical variables. … model based on multivariate logistic regression analysis. Since …

… , IQR), and categorical variables were described with number … In the testing set, we applied
three logistic regression models … biomarkers tested by UK Biobank Study with NMR technique…

… these categorical variables to numbers in order for the model … to the test set, and we saved
the training and test sets into a … Table 6, when using one-hot encoding, logistic regression, …