Enabling multivariate regression analysis is essential because researchers are typically interested in knowing how the probability of answering the sensitive question affirmatively varies as a ...

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 ...

This method, which we call multivariate regression with covariance estimation (MRCE), involves penalized likelihood with simultaneous estimation of the regression coefficients and the covariance ...

An introduction to the application of modern multivariate methods used in the social sciences, with particular focus on latent variable models (including factor analysis, structural equation models, ...

Even a change in the correlation of those parameters may indicate a problem. For that reason, multivariate monitoring, or multivariate statistics, is applied to these parameters. Multivariate analysis ...

This article will cover the theory underpinning multivariate analysis of variance (MANOVA), which expands on the capabilities of ANOVA, the types of MANOVA and a worked example of the test.

Course TopicsMultivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used ...

Multivariate analysis uses statistical tools such as multiple regression analysis, cluster analysis and conjoint analysis to determine the relationships between factors.