Sentence examples for more sophisticated multivariate from inspiring English sources

Finally, more sophisticated multivariate analysis, including multilevel regression, will be used.

A larger more diverse sample would permit more sophisticated multivariate analyses including an analysis of gender and cultural variations.

More sophisticated multivariate approaches not constrained by collinearity (e.g., partial least square regressions) need to be tested to examine further the associations between disease outcomes and ion properties.

Note that further methods could have been considered, such as the "traditional" Golub criterion or more sophisticated multivariate approaches, e.g. based on random forests [ 24].

Although a systematic SvO2 goal-oriented protocol can be statistically profitable before ICU admission, one would expect from any trained intensivist a more sophisticated, multivariate approach and a determination of the best compromise between SvO2 and its components, taking into account the specific constraints of each individual patient.

A slightly more sophisticated category of multivariate analysis is supervised methods, whereby a calibration dataset of known identity is required to build a classification model.

More sophisticated methods of multivariate GIS visualization could enhance this analysis even more but would require the Royal Thai Army to assess recruits at induction on other variables, especially risk factors, or to use recruits' home addresses rather than districts or provinces of residence.

More sophisticated methods such as multivariate analysis of whole experimental datasets[ 39, 40] can retrieve correct diffusion coefficients for mixtures containing small numbers of species, but fail completely for complex systems such as that studied here, in which a large number of different reaction products give signals in the crowded δ=3.0 6.0 ppm region.

Further studies, with more sophisticated designs and more involved multivariate analysis, are called for to directly test the hypothesis that a pleiotropic gene has a duplicated genetic effect on multiple disease phenotypes, followed by experimental or clinical validation.

The ever-increasing volume and complexity of molecular data from cancer, exemplified by the TCGA project, calls for more sophisticated analytical approaches that can detect multivariate relationships in heterogeneous data and map that information onto the existing body of knowledge of the structure of molecular networks that govern all cellular processes.

These highly-stochastic structured disease dynamics feature sudden epidemic resurgence and ample epidemic volume variability that are not easily investigated with univariate and most multivariate methods, often requiring more sophisticated approaches [e.g., 49].