Sentence examples for on multivariate regression from inspiring English sources

Hosmer Lemeshow goodness-of-fit tests were performed on multivariate regression models.

This was an independent association on multivariate regression analysis and therefore not simply driven by Medicare patients being statistically older than privately insured patients.

On multivariate regression analysis, the presence of a headache post-injury or an alteration in consciousness was significantly associated with developing PCS at 1 week and 1 month, respectively, even after controlling for age and gender.

Fourth, we propose a method based on multivariate regression to decrease the estimation errors of the number of locked on and off devices with lockout constraints, compared to [12].

On multivariate regression analysis, the presence of a headache post-injury was the most robust predictor, retaining statistical significance even after controlling for age, gender, and presence of loss of consciousness (LOC), alteration of consciousness (AOC), post-traumatic amnesia (PTA), seizure, or vomiting.

For the second category, the development of classifier design, we make a survey on various classification algorithms used in existing blind detection methods, and detail the algorithms behind several classifiers based on multivariate regression analysis, OC-SVM, ANN, CIS and Hyper-geometric structure.

The proposed method might be applied also at the end of the chain, i.e., on the demosaiced R G B bands, because estimation methods based on multivariate regressions, as those used in the present context, are insensitive of the spatial correlation of the noise[3] introduced by interpolation.

The method relies on the multivariate regression of sample mean and variance.

Based on the multivariate regression result, a sequential binary partition was performed by means of 6 variables (the 4 PTEs, Fe, and Mn) to obtain balances.

On Cox multivariate regression analysis, the prognostic significance of PIK3R1 underexpression was confirmed in the total population (p = 0.0013) and in breast cancer subgroups.

This statistical problem has been considered before, and several methods based on the multivariate regression theory, such as partial least square regression, (PLSR) and principal component regression (PCR) have been used for such situations.