Sentence examples for multivariate responses is from inspiring English sources

Modeling conditional independences in multivariate responses is an open problem.

Some new results in the theory of optimum experimental design for multivariate responses are presented.

Expressions are given for the parameter sensitivities in the transformed model and examples given of optimum designs, not only for single response models, but for experiments in which multivariate responses are measured.

In all, the data highlights day 52 (day 24 post FIVC infection) as the one in which multivariate responses are most affected by infection status.

Principal component analysis (PCA), a tool for visualizing a multivariate response, was performed on the entire gene chip and is used to illustrate differences between various groups.

Moreover, our findings with high baseline levels and low increases in cortisol associated with increasing severity of disease and organ failure were not affected by cortisol binding, and the multivariate predictors of low responses were independent of baseline cortisol and albumin levels.

Hard modeling approaches of fitting multivariate response data are based on mathematical relationships, which describe the measurements quantitatively [14]‐[16].

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

A multivariate response model was constructed to answer our research questions.

Multivariate logistic regression models for clustered responses were used to test the null hypotheses of no association between group and the two outcomes, adjusted for the stratified design and baseline imbalances between groups in significant predictors of ST use.

Designs for multivariate responses can likewise be found, requiring only the appropriate information matrix.