http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Nonparametric Regression Analysis of Longitudinal Data
This book is a research monograph in the relatively new field of nonparametric regression. It serves as an introduction to the field for graduate students, researchers and statistical consultants in statistics and biostatistics, but is also intended as an overview over some recent research developments in the fixed design case. Basic ideas are developed for various nonparametric curve estimators. The emphasis is on kernel estimators as a unifying concept and on the interplay between theory and practical application. Problems of practical application are illustrated in several examples of analyses of longitudinal medical data sets. These demonstrate the need of including nonparametric regression in addition to the classical parametric regression into the repertoire of practicing statisticians/biostatisticians. One goal of the book is to stimulate the reader to experiment with the methods and to gain experience by applying them. This is facilitated by an Appendix containing several relevant FORTRAN programs.
Introduction -- Longitudinal Data and Regression Models -- Nonparametric Regression Methods -- Kernel and Weighted Local 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 -- References.
Lecture notes in statistics (Springer-Verlag) ; 46