Sentence examples for estimation of the predictor from inspiring English sources

The process of building a robust gene expression predictor has two main steps: 1) unbiased selection of the predictor model parameters and 2) estimation of the predictor model generalisability [19].

Such an approach, however, is prone to an over-optimistic estimation of the predictor's performance due to the biased selection of the negative examples, as pointed out by Ben-Hur and Noble [ 42].

A multiple regression analysis was used for baseline estimation of the predictors of HF prevalence, due to the small incidence of new HF cases during the 7-year follow-up (5 persons).

These models account for the correlation of observations and allow estimation of the effect of predictor variables on repeated outcomes.

This model allows joint estimation of the effects of predictor variables on the 'hazard' – the risk of cessation of breastfeeding/complementary food introduction.

This model allows joint estimation of the effects of predictor variables on the risk for breastfeeding cessation rather than the duration itself [ 27].

The estimation procedure is based on estimation of the moments of the predictor and response trajectories by pooling information from all subjects.

38 Failure to accurately model serial autocorrelation may bias the estimation of the effect of predictors as well as underestimate the standard errors.

This clustering requires the use of multilevel analysis [ 19, 20], which allows for correct estimation of the standard errors of predictors in the explanatory model.

This methodology enables a quantitative estimation of relationships between the predictor variables, as well as between the predictor variables and the outcome variable.

The inclusion of a fixation baseline also allowed the estimation of HRF predictors for each of these conditions of interest (rather than simply revealing a significant difference between 2 conditions).