Sentence examples for a multivariable binary regression model from inspiring English sources
The interactions between the response to treatment (pNR vs pCR + pPR) and the variables statistically significant at univariate analysis were tested in the entire cohort and in the Luminal B/HER2− cohort in a multivariable binary regression model.
A multivariable binary logistic regression model adjusted for possible confounders (age, gender and cause of ICU admission) was carried out to define RF for ARC condition.
Variables with a p value of less than 0.1 in bivariable analyses were considered for a multivariable binary logistic regression model in order to estimate odds ratios and 95%% confidence intervals.
We used a multivariable binary logistic regression model to test our main hypotheses.
This was then extended to a multivariable binary logistic regression model in order to consider these factors simultaneously.
Univariable analysis was performed with Fisher's exact tests, which were then followed by a multivariable binary logistic regression model.
Variables with a marginal significance (P ≤ 0.20) in the univariate analyses were included in a multivariable binary logistic regression model to identify unique associations with NP symptoms.
All variables that were significant on bivariate analysis (P < 0.05) were entered in a multivariable binary logistic regression model to identify independent predictors of using alternative medicine.
For each country separately, we used a multivariable binary logistic regression model to estimate the factors associated with dying in a hospital.
Variables were introduced into a multivariable binary logistic regression model if significantly associated with mortality at day 30, using the univariate analysis when the p value was <0.2.
In case of significant differences in baseline characteristics, which may have happen by chance as we only stratify randomization by sex and center, the primary outcome will additionally be tested using a multivariable binary logistic regression model to adjust for the following potential confounders: age, acute complicated pyelonephritis, underlying co-morbidity and the use of stepdown treatment.
