Data sets that are multivariate in nature are common in modern engineering, science, and
business. In some analysis problems, univariate statistical methods applied “one variable at …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its
practical and accessible approach, with excellent examples and good guidance on …

Longitudinal data are ubiquitous across Medicine, Public Health, Public Policy, Psychology,
Political Science, Biology, Sociology and Education, yet many longitudinal data sets remain …

This second edition of Models for Repeated Measurements has been comprehensively
revised and updated, taking into account the huge amount of research that has been carried …

Growth-curve models are generalized multivariate analysis-of-variance models. The basic
idea of the models is to use different polynomials to fit different treatment groups involved in …

We present a review of the most common methods used in the analysis of longitudinal data,
briefly discussing the classical approaches and highlighting some of the more recent …

The problem of predicting a future measurement on an individual given the past
measurements is discussed under nonparametric and parametric growth models. The …

This work describes several statistical techniques for studying repeated measures data,
presenting growth curve methods applicable to biomedical, social, animal, agricultural and …

The model considered here is a generalized multivariate analysis-of-variance model useful
especially for many types of growth-curve problems, including biological growth and …