In psychology, studying multivariate dynamical processes within a person is gaining ground.
An increasingly often used method is vector autoregressive (VAR) modeling, in which each …

Data fusion is the joint analysis of multiple inter-related datasets that provide complementary
views of the same phenomenon. The process of correlating and fusing information from …

The STATIS method has been successfully applied to the analysis of sensory profiling data
and other kinds data in sensometrics. We discuss its use and benefits and compare its …

In neuroscience, clustering subjects based on brain dysfunctions is a promising avenue to
subtype mental disorders as it may enhance the development of a brain-based …

Abstract MultiLevel Simultaneous Component Analysis (MLSCA) is a data-analytical
technique for multivariate two-level data. MLSCA sheds light on the associations between …

In various areas of science, researchers try to gain insight into important processes by jointly
analysing different datasets containing information regarding common aspects of these …

Background: FMRI resting state networks (RSNs) are used to characterize brain disorders.
They also show extensive heterogeneity across patients. Identifying systematic differences …

To detect panel disagreement, we propose the clustering around latent variables for three-
way data (CLV3W) approach which extends the clustering of variables around latent …

In consumer studies, segmentation has been widely applied to identify consumer subsets on
the basis of their preference for a set of products. From the last decade onwards, a more …

In this paper, we extend the use of disjoint orthogonal components to three-way table
analysis with the parallel factor analysis model. Traditional methods, such as scaling …