Müller H.G. Nonparametric Regression Analysis of Longitudinal Data

New York: Springer, 1988. — 207 p.This monograph reviews some of the work that has been done for longitudi­ nal data in the rapidly expanding field of nonparametric regression. The aim is to give the reader an impression of the basic mathematical tools that have been applied, and also to provide intuition about the methods and applications. Applications to the analysis of longitudinal studies are emphasized to encourage the non-specialist and applied statistician to try these methods out. To facilitate this, FORTRAN programs are provided which carry out some of the procedures described in the text. The emphasis of most research work so far has been on the theoretical aspects of nonparametric regression. It is my hope that these techniques will gain a firm place in the repertoire of applied statisticians who realize the large potential for convincing applications and the need to use these techniques concurrently with parametric regression. This text evolved during a set of lectures given by the author at the Division of Statistics at the University of California, Davis in Fall 1986 and is based on the author's Habilitationsschrift submitted to the University of Marburg in Spring 1985 as well as on published and unpublished work. Completeness is not attempted, neither in the text nor in the references.Longitudinal Data and Regression Models
Nonparametric Regression Methods
Kernel and Local Weighted Least Squares Methods
Optimization of Kernel and Weighted Local Regression Methods
Multivariate Kernel Estimators
Choice of Global and Local Bandwidths
Longitudinal Parameters
Nonparametric Estimation of the Human Height Growth Curve
Further Applications
Consistency Properties of Moving Weighted Averages
Fortran Routines for Kernel Smoothing and Differentiation