Sentence examples for predictors and its from inspiring English sources

Dominance analysis addresses these issues by accounting for a variable's direct effect (when considered alone), its total effect (conditional on all other predictors), and its partial effect (conditional on subsets of predictors) in terms of its contribution to overall variance.

It provides an opportunity to examine IH and both its structural predictors and its associations with HIV risk behaviour in a large and geographically diverse sample, with sufficient countries to enable analysis by country-level (macro) as well as local-level (meso) and individual-level (micro) variables.

For systems, where the delay is dominant (i.e., the delay is big compared with the time constant of the system), different control strategies such as delay compensation schemes (DCS) should be used, being the most well-known the Smith predictor and its modifications for unstable and integrative systems [8 11].

At time k, the KF state predictor and its error covariance are obtained as x ̂ k | k - 1 = F k x ̂ k - 1 | k - 1 P k | k - 1 = F k P k - 1 | k - 1 F k T + Q k. (8).

The AME is the adjusted difference in prevalence of outcome (in %) between given category of predictor and its reference group.

In addition to the specific predictor and its interaction with time, models include participant age and sex and their interactions with time.

The findings of this study indicate that the Konkoor is not a consistent predictor, and its predictive validity declines over the academic years in medical school.

A p-value for interaction terms > 0.05 will be used to remove both the predictor and its interaction from the model.

GLMM generates separate estimates for an individual predictor and its group-level mean [ 26], allowing separation of random effects from fixed effects.

The assumption of linearity of the logit was also met (the logistic regression was run with the interaction terms of each continuous predictor and its log, none of which were significant predictors).

(2011) in the sense that we improved upon the choice of the change point predictor and its selection, and improve the modelling with respect to the distributional assumptions for the conditional response and the random effects.