Sentence examples for multivariate regression followed from inspiring English sources

The importance of biosynthetic cost in explaining gene expression at the protein level was also assessed using multivariate regression followed by variable removal using the same strategy as for transcript levels above.

Selection of marker genes by either moderated t-test or multivariate LASSO regression followed by LDA or logistic regression, are robust approaches to classification with omics data, confirming in part findings of previous sbv IMPROVER challenges.

In the stepwise multivariate regression that followed, all organisational variables and all potential interactions were included.

We used univariate logistic regression, followed by multivariate backward conditional logistic regression to obtain adjusted odds ratios (AOR) and associated 95%% confidence intervals.

To identify risk factors for pterygium, we applied univariate logistic regressions followed by multivariate logistic regressions.

Results of the multivariate regression analyses at follow-up showed a similar pattern (Additional file 1: Table S1 and Additional file 2: Table S2): only the length of hospitalization duration and the parents' educational level had a statistically significant impact on at least 4 scores; different other factors specifically affected various IBHQ-FU scores.

Following multivariate regression analysis, two variables were significant at P ≤ 0.05.

Univariate or unadjusted regression analysis was followed by multivariate regression where patient characteristics found to be significantly associated with the total number of transitions, at the 0.05 level of significance in the unadjusted analysis were included in the initial model.

To detect predictive variables for treatment responders at 12-weeks follow-up multivariate regression analyses will be used.

Statistical comparisons between categorical variables were made using the chi-square test for univariate analysis followed by multivariate regression.

Univariate analysis was performed between potential risk factors and mortality followed by multivariate regression analysis to ascertain independent predictors of mortality.