The phrase "approach for multivariate" is not complete and lacks clarity in written English.
It can be used in contexts related to statistical analysis or research methodologies that involve multiple variables.
Example: "We need to develop a new approach for multivariate analysis to better understand the data patterns."
Alternatives: "method for multivariate" or "strategy for multivariate".
The approach for multivariate Cox modeling was to (1) obtain a model by allowing entry of only genetic features, (2) include all significant interactions after testing all possible pairs of interactions among significant genetic factors selected by multivariate Cox regression, and finally (3) adjust this model for age, ISS, and study site to obtain a final composite model for outcome.
Fan and Wang (2009), Liu et al. (2010) used the same approach for multivariate failure time data with auxiliary covariates.
The origin of PCA can be traced back to 1901 [14] and it is an approach for multivariate analysis.
We propose a new standardised approach for multivariate community analyses on ecosystem scale, based on a combined data matrix from different taxonomic groups.
The above is a standard analysis and plotting approach for multivariate data, but since this analysis has been driven by the principals of GM that maintain the relationships in physical space amongst the variables, these results can be used to construct hypothetical configurations of landmarks representing arbitrary points in the space of principal components.
A natural extension of the previous approach for multivariate data is to extract the intersection among inverse images of multiple function values first, and then track the topological changes inherent in that intersection with respect to the multivariate function value changes.
Hierarchical clustering analysis (HCA) is one of the most commonly used approaches for multivariate analysis, which can classify the objects (samples) into classes (clusters) by means of measuring either the distance or the similarity between the objects.
Our approach allows for multivariate determinants and multi-location choices of net migration flows.
As a conditional first order linearization approach provides the least biased estimate in estimating the PK parameter with comparable efficiency [ 22, 23]), it is chosen as the estimation approach for this multivariate nonlinear mixed model.
A stepwise backward regression approach was used for multivariate analysis.
A time-independent Cox proportional hazard approach was used for multivariate survival analysis using all variables of the univariate analysis (Table 2).
