Analysis and Interpretation of Multivariate Data

Multivariate analysis is concerned with the interrelationships among several variables. The data may be metrical, categorical, or a mixture of the two. Multivariate data may be, first, summarized by looking at the pair-wise associations. Beyond that, the different methods available are designed to explore and elucidate different features of the data. The article briefly summarizes the scope and purpose of the following methods: cluster analysis, multidimensional scaling, principal components analysis, latent class analysis, latent profile analysis, latent trait analysis, factor analysis, regression analysis, discriminant analysis, path analysis, correspondence analysis, multilevel analysis, and structural equation analysis.