Introduction -- Parametric and semiparametric methods -- Kernel and local polynomial methods -- Basis approximation smoothing methods -- Penalized smoothing spline methods -- Smoothing with time-invariant covariates -- The one-step local smoothing methods -- The two-step local smoothing methods -- Global smoothing methods -- Models for concomitant interventions -- Nonparametric mixed-effects models -- Unstructured models for distributions -- Time-varying transformation models-I -- Time-varying transformation models-II -- Tracking with mixed-effects models
Summary
"This book covers the recent advancement of statistical methods for the analysis of longitudinal data. Real datasets from four large NIH-supported longitudinal clinical trials and epidemiological studies illustrate the practical applications of the statistical methods. This book focuses on the nonparametric approaches, which have gained tremendous popularity in biomedical studies. These approaches have the flexibility to answer many scientific questions that cannot be properly addressed by the existing parametric approaches, such as the linear and nonlinear mixed effects models."-- Provided by publisher
Notes
"A Chapman & Hall book."
Bibliography
Includes bibliographical references (pages 529-539) and index
Notes
Description based on online resource; title from PDF title page (Site, viewed 09/03/2020)
