Sentence examples for multivariable comparisons were from inspiring English sources

Multivariable comparisons were completed using conditional logistic regression.

Matched bivariable comparisons and multivariable comparisons were completed using conditional logistic regression.

Multivariable comparisons were performed using Proc GLIMMIX least squares means controlled for the random effect of study center, and all P values were two sided, with P < 0.05 considered significant.

In these multivariable analyses, 140 comparisons were made (14 exposures with 5 outcomes and 2 models).

Multiple statistical comparisons were performed using ANOVA in a multivariable linear model.

To determine independent correlates of sleep quality, variables that were correlated in bivariate comparisons were then included in a series of multivariable linear regression models.

Bivariate comparisons were performed on the unmatched groups and multivariable regression analyses were performed on the matched groups.

All comparisons were 2-tailed and a variable was considered statistically significant if it had a p-value < 0.01 in the final multivariable model.

Logistic regression was used for multivariable comparisons with backward deletion from first step models including variables significant at 0.1 level in the univariable analysis.

For comparisons of hospitalisation rates and multivariable comparisons of risks of hospitalisation, all patients were followed from 1 January 1997 and allocated to the non-AF population until a first hospitalisation for AF.

The log-rank test and proportional hazards models were used for univariable and multivariable comparisons of PFS and OS.