Sentence examples for multivariate response variable from inspiring English sources

Related unadjusted and adjusted treatment effect estimates for the multivariate response variable are also found and their properties discussed.

To briefly summarize the methodology described in Wilson et al. [13], CCA models were developed, based on a 1/8th subsample of the plots, that related the multivariate response variable measured on the field plots (live tree basal area by species) with the associated 21 predictor variables extracted from the raster stack at each plot location.

To briefly summarize the methodology described in Wilson et al. [ 13], CCA models were developed, based on a 1/8th subsample of the plots, that related the multivariate response variable measured on the field plots (live tree basal area by species) with the associated 21 predictor variables extracted from the raster stack at each plot location.

We tested for flow regulation effects on 17 (univariate and multivariate) response variables representing fish population abundance and assemblage characteristics using a field design based on the environmental flow assessment framework known as ELOHA (Ecological Limits of Hydrologic Alteration).

In OPLSDA, a regression model is calculated between the multivariate data and a response variable that only contains group information.

In all regressions, the 8 PCs associated with NEFD defined the multivariate response and the independent variables considered were: the bio-anthropometric, height and population.

These methods involve a hierarchical decomposition of a multivariate response function in terms of variables with increasing dimensions and score functions associated with probability distribution of a random input.

It is worth noting from the multivariate response model that the socioeconomic variables of interest had stronger associations with physical functioning (accounting for 24% of variation) than psychological well-being (accounting for 7% of total variation).

To identify factors independently associated with the response variable, we used backward-elimination multivariate regression analysis with p>0.05 as the defining criteria for exclusion of model terms.

Unconditional maximum likelihood estimation of the multivariate logistic regression was also performed for each response variable by using backward elimination method at a 0.05 significance level.

The multivariate analysis will depend on the nature of the response variable.