This paper presents an overview of methods for the analysis of data structured in blocks of
variables or in groups of individuals. More specifically, regularized generalized canonical …

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study
emotions in interpersonal interaction are limited because stationarity is assumed. This …

Multiblock Data Fusion in Statistics and Machine Learning Explore the advantages and
shortcomings of various forms of multiblock analysis, and the relationships between them …

Older adults are often described as being more emotionally competent than younger adults,
and higher levels of affect complexity are seen as an indicator of this competence. We …

Psychological research often builds on between-group comparisons of (measurements of)
latent variables; for instance, to evaluate cross-cultural differences in neuroticism or …

To explore structural differences and similarities in multivariate multiblock data (eg, a
number of variables have been measured for different groups of subjects, where the data for …

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 …

The issue of measurement invariance is ubiquitous in the behavioral sciences nowadays as
more and more studies yield multivariate multigroup data. When measurement invariance …

Given multivariate data, many research questions pertain to the covariance structure:
whether and how the variables (eg, personality measures) covary. Exploratory factor …

We address the problem of analyzing one or several blocks of variables measured on the
same individuals which are a priori divided into several groups. In this framework, we focus …