Sentence examples for multivariate analysis modelling from inspiring English sources

Likewise, in a multivariate analysis modelling for OS, the same parameters age, stage and a segmental genomic type were retained in the model (P<0.0001 and RR=4.6; P<0.0001 and RR=3.1; P=0.05 and RR=1.8, respectively).

In multivariate analysis modelling EFS, the parameters age, stage and a segmental genomic type were retained in the model, whereas the individual genetic markers were not (P<0.0001 and RR=2.56; P=0.0002 and RR=1.8; P=0.01 and RR=1.7, respectively).

In a multivariate analysis modelling for EFS, the parameters age >18 months, stage 4 disease and a segmental genomic type were associated with a higher risk of relapse, whereas the individual genetic markers and ploidy were not (P<0.0001 and RR=2.6; P=0.0002 and RR=1.8; P=0.01 and RR=1.7, respectively, Table 3).

Multivariate analysis modelled a target phenotype vector, accounting for individual correlation between vector entries.

The complex multivariate analysis models that emerge require more sophisticated statistical analysis.

In case a potential mediator is inserted into multivariate analysis (Model II), the effect of the treatment (C′) should disappear.

Its subclasses comprise a univariate analysis model, bivariate analysis model, and multivariate analysis model by cardinality of the quality data representation slot.

Multivariate analyses such as multiple regression, factor analysis, and principal component analysis are defined as subclasses of the multivariate analysis model.

The results are demonstrated for both block and fast single-event task designs, applied to standard univariate and adaptive multivariate analysis models.

The study employed a multivariate analysis model incorporating factors associated exclusively with the library's operation (endogenous factors) and factors associated with the academic and cultural context in which the library operates (exogenous factors).

Correlations were examined by calculating the Pearson linear correlation coefficient and a multivariate analysis model was used to adjust for age and gender.