Sentence examples for binary logistical regression model from inspiring English sources

OR (95% CI) and Siga, Sigb value were calculated using a binary logistical regression model adjusted for sex, age, smoking, and drinking with normal versus non-dampness-phlegm, normal versus dampness-phlegm.

Multivariate binary logistical regression models predicting disease severity were constructed using patient characteristics, adjusted NPA cytokine concentrations and adjusted NPA hRSV load (table 3).

Multivariate binary logistical regression models were constructed for two previously accepted definitions of severe disease "any need for supplemental oxygen including ventilation" and "any need for mechanical ventilation" [11], [22], [23].

We will use descriptive data analysis along with t-tests, chi-square tests, Mann–Whitney-U tests, and multivariate linear and binary logistical regression models.

Binary logistic regression model was used for analysing data.

Univariate and multivariate analysis were conducted using binary logistic regression model.

Binary logistic regression model was estimated using the Entry method.

As confirmation, we used a binary logistic regression model.

Multivariate analyses were performed using a binary logistic regression model.

We found this odd, since assumptions for statistical models are quite distinct (binary logistic regression model vs. linear regression model).

The primary outcome (global assessment of outcome) will be modelled using a binary logistic regression model.