Sentence examples for multivariate survival models from inspiring English sources

The SI score outperformed tumor grade and pleural invasion in univariate (Table 2) and/or multivariate survival models (Table 3).

Univariate and multivariate survival models were constructed along with multivariate logistic regression models to find independent predictors of spontaneous renal recovery.

For multivariate survival models, a Cox regression analysis was used to identify independent prognostic factors.

Currently, the short follow-up did not enable a construction of sensible multivariate survival models.

Univariate and multivariate survival models were assessed using the Cox proportional hazards regression model and the LRT.

As multivariate survival models using microarray data are prone to overfitting, we built the model by combining the univariate Cox models computed during feature selection [ 8].

Cox's proportional hazards model was used to fit the multivariate survival model.

To assess the performance of the multivariate survival model, a leave-one-out cross-validation (LOOCV) analysis was performed.

Therefore we included C-reactive protein in addition to TNM stage, treatment and appetite loss in the multivariate survival model.

In a multivariate survival model, SpO2 > 90% and patient scores on the LCSS appetite and fatigue subscales were independent predictors of survival.

However, when a multivariate survival model was chosen, only eosinophils had a significant effect once clinical stage was included in the model.