Sentence examples for multivariate multiple regression from inspiring English sources
A multivariate multiple regression analysis predicting each of the PTGI items was conducted with young adults who experienced the Great East Japan Earthquake (N = 316).
Multivariate multiple regression analyses failed to reveal any significant relationship between soil physico-chemical variables and shifts in soil PLFA profiles.
This study proposes a multivariate bias correction technique based on canonical correlation analysis (CCA) - a dimension reduction technique based on multivariate multiple regression - that reduces the bias in both streamflow and loadings simultaneously by preserving the cross-correlation.
We employed multivariate multiple regression models to evaluate sediment and topographic heterogeneity, canyon transverse profiles, and overall water mass variability as potential drivers of macrobenthic community structure and species richness.
The population model, which describes the distribution of the latent variables and the relationship between the contextual variables and the latent variables, is a multivariate multiple regression model, where γ are the regression coefficients that are estimated, Σ is the conditional covariance matrix, and W are the contextual variables.
The multivariate, multiple regression analyses indicated that quantity and quality of organic matter explained an important portion of the variances of the diversity indices, but also temperature and physicochemical conditions played an important role in determining the observed patterns.
When crosschecking the significant variables from both models, it was found that both risk factors identified by the forward-entry BRT model were significantly associated with disease occurrence when analyzed using the multivariate logistic multiple regression, but yielded a lower AUC than the variable selected directly by the multivariate logistic regression.
A multivariate multiple linear regression (MMLR) analysis was applied to determine the relationship between environmental and mobility measurements.
In another work, Eyvazian et al. (2011) proposed a method based on the likelihood ratio approach to estimate the time of a step change in the parameters of a multivariate multiple linear regression profile in Phase II.
In fact, the rapid multivariate multiple linear regression (RMMLR) method proposed by Basu et al. is essentially equivalent to the multivariate gene-based CCA/MANOVA proposed by Tang and Ferreira, leaving only one MANOVA-based method.
In this paper, we have demonstrated the use of a novel multivariate multiple linear regression method, to determine relative contributions of various genomic traits explaining different aspects of gene expression.
