Multivariate Clustering Analysis in R Course Topics Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration.

The primary goal of this short course is to help researchers with multivariate data better visualize and understand their data using multivariate analysis tools. In this course, we will focus on ...

Thomas R. Ten Have, A Mixed Effects Model for Multivariate Ordinal Response Data Including Correlated Discrete Failure Times with Ordinal Responses, Biometrics, Vol. 52, No. 2 (Jun., 1996), pp.

The following topics will be covered: principal components analysis, exploratory factor analysis, confirmatory factor analysis, structural equation models, latent class models and latent trait models.

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 ...

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 ...

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 ...