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