Multivariate statistical inference encompasses methods that evaluate multiple outcomes or parameters jointly, allowing researchers to understand complex interdependencies within data. Permutation ...

This paper describes a method for a model-based analysis of clinical safety data called multivariate Bayesian logistic regression (MBLR). Parallel logistic regression models are fit to a set of ...

Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SAS Software, Second Edition provides a unique approach to the topic, integrating ...

In the setting of nonparametric multivariate regression with unknown error variance σ², we study asymptotic properties of a Bayesian method for estimating a ...

Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

MANOVA is a statistical test that extends the scope of the more commonly used ANOVA, that allows differences between three or more independent groups of explanatory (independent or predictor) ...

I actively involve in professional and academic activities such as serving as frequent referees for peer-reviewed statistical journals such as: Journal of the Royal Statistical Society (Series B and C ...

Multivariate 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 for several ...