Sentence examples for multivariate analyses binary from inspiring English sources

Univariate and multivariate analyses (binary logistic regressions) were performed to identify the ability of different variables to predict ICU mortality, calculating the odds ratios and their respective 95% confidence intervals.

We first performed bivariate analyses to look for crude associations in the data, followed by Mantel-Haenszel analyses, before going on to complete multivariate analyses using binary logistic regression modelling.

Results from the multivariate analyses using binary logistic regression model showed that male sex, overweight and short sleep duration were found to be independent risk factors for hypertension (Table  3).

Univariate and multivariate analyses using a binary logistic regression were used to identify factors associated with the dependent variable (hospital mortality).

Multivariate analyses were performed using binary logistic regression with estimation of odds ratios (OR) and 95% confidence intervals (95%CI).

For multivariate analyses, we used a binary logistic regression.

Multivariate analyses were based on binary logistic regression.

Multivariate analyses were conducted using binary logistic regression to examine the association between smoking and CRS after adjusting for socio-demographic factors.

The univariate and multivariate analyses were performed by binary logistic regression model to estimate the odds ratio (OR) and 95% confidence interval (95% CI).

Multivariate analyses were performed by binary logistic regression, defining TP53- and CHEK2 mutations as categorical variables and ATM mRNA levels as a continuous variable.

Patient data was reported using bivariate (χ, Fishers Exact test, Wilcoxon Rank Sum with Bonferroni correction, and non parametric Kruskal-Wallis ANOVA) and multivariate analyses (logistic regression with binary outcome variables) to assess FABP-1 staining and clinical characteristics.