Applied longitudinal Data Analysis

The goal of this book is to provide an overview of statistical models and methods that are useful in the analysis of longitudinal data; that is, data in the form of repeated measurements on the same experimental unit over time. The intended audience is a combination of non- statistics graduate students who have taken an applied methods course covering linear regression and Analysis of Variance and masters-level statistics students looking for an applied intro course.

Inhalt
Introduction and Motivation * Review of Matrix Algebra * Random Vectors and Multivariate Normal Distribution * Univariate Repeated Measures Analysis of Variance * Multivariate Repeated Measures Analysis of Variance * Drawbacks and Limitations of Classicial Methods * General Linear Models for Longitudinal Data * Random Coefficient Models for Multivariate Normal Data * Linear Mixed Effects Models for Multivariate Normal Data * Generalized Linear Models for NonNormal Response * Population-averaged Models for Nonnormal Repeated Measurements * Advanced Topics