Non-parametric and semi-parametric regression methods: Introduction and overview Chapter

abstract

• 2009 by Taylor & Francis Group, LLC. Parametric regression methods for longitudinal data have been well developed in the last 20 years. Such methods can be classified broadly as estimating equation based methods, such as generalized estimating equations (Liang and Zeger, 1986), and their extensions (Chapter 3), and mixed-effects models (Laird and Ware, 1982; Breslow and Clayton, 1993; see also Chapter 4). Diggle et al. (2002) provide an excellent overview of these parametric regression methods. For recent developments, see Chapter 3 through Chapter 6.

authors

• Carroll, Raymond

author list (cited authors)

• Lin, X., & Carroll, R. J.

complete list of authors

• Lin, Xihong||Carroll, Raymond J

Book Title

• LONGITUDINAL DATA ANALYSIS

publication date

• January 2009

published in

• n2379-2396ISSN  Journal

International Standard Book Number (ISBN) 13

• 978-1-58488-658-7

start page

• 191

end page

• 197