Sentence examples for integrated regression model from inspiring English sources
An integrated regression model that incorporated 3D pose and 3D motion models into the GPR model described in this paper would likely improve the robustness of both weak pose estimation and action recognition.
It is no coincidence that some recent developments in regression modelling have been marked by the efforts to integrate regression with a variety of covariance structure models [ 1- 3].
Each factor resulting from the factor analysis was integrated into a regression model in order to identify the predictive covariates of responsibility (Table 5).
HADS scores and diagnosis were also integrated in the regression models (data not shown) but did not add any relevant effect.
For each arm, comparison of outcome changes between pre- and post-intervention periods will be computed using a GEE regression model, integrating the clustering of children by department.
After the identification of age, skin type, and number of nevi as independent demographic and phenotypic melanoma risk factors in our study group [ 9, 48], we analyzed every single SNP for its association with melanoma risk in a dominant as well as an additive logistic regression model integrating these risk factors.
Using those variables, we calculated the PS for receiving complete Children's Treatment Network (CTN) integrated care by a logistic regression model.
In step 2, the variables selected in the four regression analyses in the previous step were integrated into one multiple-linear regression model explaining general health as measured by item 1 of the SF-36.
Methods of calculating Newmark displacement and integrating all factors into a regression model are both presented and discussed.
In this paper, we use the enhanced L1/2 solver to penalized network-constrained logistic regression model to integrate lung cancer gene-expression with protein-to-protein interaction network.
The sample size, based on aforementioned ratio between both groups (choice of procedure), needs to be large enough to be able to integrate these confounders into a regression model.
