Multiple response questions, also known as a pick any/J format, are frequently encountered in the analysis of survey data. The relationship among the responses is difficult to explore when the number ...

The issues of model-based clustering and classification of longitudinal data have received increasing attention in recent years. In this paper, we propose a finite mixture of multivariate t linear ...

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

An introduction to the application of modern multivariate methods used in the social sciences, with particular focus on latent variable models for continuous observed variables, and their application ...

Multivariate analysis of variance (MANOVA) is an extension of the commonly used analysis of variance (ANOVA) method, allowing statistical comparisons across three or more groups of data and involving ...

Research methods suitable for the analysis of big datasets containing many variables. The fundamentals of data visualisation, customer segmentation, factor analysis and latent class analysis with ...

Statistics are often viewed as confusing and complicated, but multivariate data analysis (MVA) methods can be used to amass knowledge simply.

Multivariate data analysis (MVDA) is being used to effectively handle complex datasets generated by process analytical technology (PAT) in biopharmaceutical process development and manufacturing.