Sentence examples for predictors from which from inspiring English sources

Research on cerebellar haemorrhage so far has focused on identifying outcome predictors from which treatment algorithms can be derived.

This strategy was chosen, as within the same cross-validated risk set the index values vary depending on the set of predictors from which they originate.

14 A prediction or prognostic algorithm is not about searching for new risk factors; it is a combination of multiple known predictors from which risk of a specific endpoint can be calculated for individual patients.

The following models, if fitted using the Cox proportional hazards model, correspond to those developed by Tudur-Smith et. al. [ 14], which are estimated by maximising the penalized partial likelihood to find the best linear unbiased predictors, from which the REML estimators of the variance components were found [ 27].

Correlation coefficients between predictor variables and measures from which predictor variables were derived are shown in Table 2. Predictor variables were correlated strongly with the measures from which they were derived (mean r = 0.87) but weakly with the other measures (mean = 0.17; t(21) = 15.47, P < 0.0001).

In essence, we were left with a choice whether to include the predictors for which we had expectations (from a theoretical point of view) or to replace them with other possible important covariates.

Hence, the baseline HIV genotype (from which most predictors are derived) ceased to determine the clinical response at later points in time.

Fortunately, numerous papers contain baseline population characteristics from which univariable predictor-outcome associations can be derived.

R is known as a Toeplitz Matrix with the size of p∗ p from which the predictor coefficients can be calculated by inverting the matrix R, A = − R−1 r.

Frequently, investigators will approach the issue in two distinct stages: first, by testing whether the new predictor variable is significant in a multivariable regression model; second, by testing differences between the AUC of models with and without the predictor using the same data from which the predictive models were derived.

Typically the secondary structure predictors generate lists of suboptimal structures from which it is difficult to extract the best ones.